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1
Ghasemzadeh, Fereidoun. "Project portfolio selection : a decision support approach /". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0003/NQ42738.pdf.
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2
Chamberlain, Matthew Kipp. "An Approach to Decision Support for Strategic Redesign". Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19838.
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Researchers have paid relatively little attention to the fact that most design activities are actually more like redesign. These activities are characterized by an attempt to leverage experience, knowledge, and the capital that a company has already invested into existing engineering systems. In this dissertation, it is proposed that an approach be developed to aid designers in making decisions in redesign problems when there exist systems to be leveraged and multiple new systems to be created. In addition, strategy is introduced to the problem through the consideration that new systems may not be offered all at once, as is often assumed in product family design research. In this dissertation, the aim of the designer is assumed to be a creation, through redesign, of a series of new systems with desirable and distinct performance levels. In addition, a plan is required to involve as little redesign effort throughout the life of the family of systems as possible
The proposed approach is based upon the concepts of Constructal Theory and previous work to create methods for the design of mass customized families of products. The existing methods are abstracted and heavily modified through the infusion of the compromise Decision Support Problems at all stages of the decision-making process. In addition, two indices are developed to represent considerations unique to redesign as opposed to original design. These indices for redesign effort and commonality value are utilized in the overall objective formulation for the approach. Through a thorough validation process and a large number of redesign scenarios, it is shown that the overall approach proposed can lead the designer towards promising redesign plans involving leveraging of existing systems, but that the constructal-inspired approach in and of itself has certain limitations when applied to redesign.
3
Burd, Elizabeth L. "Reuse with risk management : a decision support approach". Thesis, University of York, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247526.
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Osop, Hamzah Bin. "A practice-based evidence approach for clinical decision support". Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/123320/2/Hamzah%20Bin%20Osop%20Thesis.pdf.
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This thesis studies the conceptualisation and evaluation of a Practice-Based Evidence approach to decision making in healthcare. It examines the existing ICT architecture of a public hospital in Singapore to design a decision support system that leverages practical clinical evidence meaningfully captured in electronic health records. In doing so, healthcare professionals are supported in decision making through findings from past similar patients that can be generalised to the current patient population.
5
Khan, Q. "A computer graphics approach to logistics strategy modelling". Thesis, Cranfield University, 1990. http://dspace.lib.cranfield.ac.uk/handle/1826/4755.
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This thesis describes the development and application of a decision support
system for logistics strategy modelling. The decision support system that is
developed enables the modelling of logistics systems at a strategic level for
any country or area in the world. The model runs on IBM PC or compatible
computers under DOS (disk operating system).
The decision support system uses colour graphics to represent the different
physical functions of a logistics system. The graphics of the system is machine
independent. The model displays on the screen the map of the area or country
which is being considered for logistic planning.
The decision support system is hybrid in term of algorithm. It employs
optimisation for allocation. The customers are allocated by building a network
path from customer to the source points taking into consideration all the
production and throughput constraints on factories, distribution depots and
transshipment points.
The system uses computer graphic visually interactive heuristics to find the
best possible location for distribution depots and transshipment points. In a
one depot system it gives the optimum solution but where more than one
depot is involved, the optimum solution is not guaranteed.
The developed model is a cost-driven model. It represents all the logistics
system costs in their proper form. Its solution very much depends on the
relationship between all the costs. The locations of depots and transshipment
points depend on the relationship between inbound and outbound
transportation costs.
The model has been validated on real world problems, some of which are
described here. The advantages of such a decision support system for the
formulation of a problem are discussed. Also discussed is the contribution of
such an approach at the validation and solution presentation stages.
6
Muya, Mundia. "A systematic approach for improving construction materials logistics". Thesis, Loughborough University, 1999. https://dspace.lboro.ac.uk/2134/7076.
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In the 1990s, the UK construction industry directed considerable effort at improving productivity and reducing costs by harmonising relationships among clients, contractors, sub-contractors, specialist contractors and designers. Opportunities to accrue further benefits should be explored and capitalised upon from all areas of construction projects. Management of construction materials on well grounded logistics and supply chain management principles has the potential to yield results and augment efforts being made in other areas at making construction more efficient. The overall aim of this thesis was to develop a systematic supplier management decision-support process model that contractors can use for both short and long-term management of suppliers in the implementation of construction materials supply logistics. Such a process model would benefit construction companies by identifying essential elements that lead to improved supply of construction materials. The research findings were based upon a literature survey, two `minor-image' questionnaires (one sent to 71 UK contractors and the other to 76 UK construction materials suppliers); structured interviews with nine UK contractors and five UK construction materials suppliers; and a supplier management process model validation exercise with six UK contractors. From these, the research produced the following outcomes: systematic supplier management decision-support process map that contractors can use for short and long-term management of suppliers in the implementation of construction materials supply logistics; an understanding of the supply of construction materials into construction processes from the wider perspective of logistics and supply chain management as opposed to traditional materials management; the identification of the performance indicators against which the performance of suppliers can be evaluated and the quantification of the relative contribution of the performance indicators to improvements in customer service; the identification of factors which enable suppliers to improve levels of customer service and quantification of the relative extent to which the factors enable suppliers to contribute to improvements in their levels of customer service in the delivery of construction materials; identification of the extent to which both performance indicators and enablers were used in supplier evaluation and selection; evaluation and comparison of the extent to which contractors and suppliers used information and communication technologies in internal and external materials supply logistics processes; and evaluation of the nature of relationships between contractors and suppliers.
7
Pedersen, Kim Ohme. "Explanation Methods in Clinical Decision Support : A Hybrid System Approach". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11833.
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The use of computer-based decision support systems within the field of health science has over the last decades been extensively researched and tested, both in controlled environments and in clinical practice. Despite the obvious benefits of utilizing such systems in the day-to-day activities, many of the designed systems fail to make the impact one could hope to achieve. We have designed and implemented a prototype of a decision support system which use both Case-Based Reasoning and probabilistic inference through a Bayesian Network as a basis for the solution. To achieve user acceptance an explanation module has been implemented which gives the user full access to the data which has been used in the reasoning process, both from the Case-Based Reasoning and the Bayesian Network. The system has shown promising results within the domain of wine recommendation, with a very high accuracy despite uncertain accuracy of the knowledge within the system. Furthermore the explanations presented to an expert conformed to the causal way of reasoning used by said expert, and was accepted as a very useful tool to get pointed in the right direction for evaluation of the solution.
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Nwiabu, Nuka D. "Situation awareness approach to context-aware case-based decision support". Thesis, Robert Gordon University, 2012. http://hdl.handle.net/10059/791.
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Context-aware case-based decision support systems (CACBDSS) use the context of users as one of the features for similarity assessment to provide solutions to problems. The combination of a context-aware case-based reasoning (CBR) with general domain knowledge has been shown to improve similarity assessment, solving domain specific problems and problems of uncertain knowledge. Whilst these CBR approaches in context awareness address problems of incomplete data and domain specific problems, future problems that are situation-dependent cannot be anticipated due to lack of data by the CACBDSS to make predictions. Future problems can be predicted through situation awareness (SA), a psychological concept of knowing what is happening around you in order to know the future. The work conducted in this thesis explores the incorporation of SA to CACBDSS. It develops a framework to decouple the interface and underlying data model using an iterative research and design methodology. Two new approaches of using situation awareness to enhance CACBDSS are presented: (1) situation awareness as a problem identification component of CACBDSS (2) situation awareness for both problem identification and solving in CACBDSS. The first approach comprises of two distinct parts; SA, and CBR parts. The SA part understands the problem by using rules to interpret cues from the environment and users. The CBR part uses the knowledge from the SA part to provide solutions. The second approach is a fusion of the two technologies into a single case-based situation awareness (CBSA) model for situation awareness based on experience rather than rule, and problem solving predictions. The CBSA system perceives the users’ context and the environment and uses them to understand the current situation by retrieving similar past situations. The futures of new situations are predicted through knowledge of the history of similar past situations. Implementation of the two approaches in flow assurance control domain to predict the formation of hydrate shows improvements in both similarity assessment and problem solving predictions compared to CACBDSS without SA. Specifically, the second approach provides an improved decision support in scenarios where there are experienced situations. In the absence of experienced situations, the second approach offers more reliable solutions because of its rule-based capability. The adaptation of the user interface of the approaches to the current situation and the presentation of a reusable sequence of tasks in the situation reduces memory loads on operators. The integrated research-design methodology used in realising these approaches links theory and practice, thinking and doing, achieving practical as well as research objectives. The action research with practitioners provided the understanding of the domain activities, the social settings, resources, and goals of users. The user-centered design process ensures an understanding of the users. The agile development model ensures an iterative work, enables faster development of a functional prototype, which are more easily communicated and tested, thus giving better input for the next iteration.
9
Lewis, Richard. "A semantic approach to railway data integration and decision support". Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5959/.
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The work presented in this thesis was motivated by the desire of the railway industry to capitalise on new technology developments promising seamless integration of distributed data. This includes systems that generate, consume and transmit data for asset decision support. The primary aim of the research was to investigate the limitations of previous syntactic data integration exercises, creating a foundation for semantic system development. The objective was to create a modelling process enabling domain experts to provide the information concepts and semantic relationships between those concepts. The resulting model caters for the heterogeneity between systems supplying data that previous syntactic approaches failed to achieve and integrate data from multiple systems such that the context of data is not lost when centralised in a repository. The essence of this work is founded on two characteristics of distributed data management; the first is that current Web tools, like XML, are not effective for all aspects of technical interoperability because they do not capture the context of the data; and second, there is little relationship between conventional database management systems and the data structures that are utilised in Web based data exchange which means that a different set of architecture components are required.
10
Voightmann, Michael P. (Michael Paul) 1979. "Generating quality software specifications for decision support : a novel approach". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/17836.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.Includes bibliographical references (leaves 70-74).
An approach utilizing cognitive support tools is presented with the purpose of improving upon the generation of quality software requirement specifications. Based on successful tools in product development and cognitive engineering, the framework suggests how to improve upon user comprehension by the creation of decision support tools. These tools can facilitate the construction of a well-structured system map, incorporating key cognitive aspects, as well as identifying hidden requirements. Minimizing the requirements errors early in the process can have a tremendous impact on the success of the project. Current practices have been unable to improve upon the large failure rate of software systems. They generally lack the structure that cognitive support tools can provide. In order to assess the proposed approach, an overview of the current state of software requirements practice is provided. Key product development and cognitive support approaches were then analyzed. The proposed approach is described, followed by suggestions for future tools that could have a great impact on requirements engineering. Finally, the proposed approach is evaluated by applying it to an automotive application: adaptive cruise control.
by Michael P. Voightmann.
S.M.
11
Sannellappanavar, Vijaya Laxmankumar. "DATAWAREHOUSE APPROACH TO DECISION SUPPORT SYSTEM FROM DISTRIBUTED, HETEROGENEOUS SOURCES". University of Akron / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=akron1153506475.
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Evans, Liam. "Experience-based decision support methodology for manufacturing technology selection : a fuzzy-decision-tree mining approach". Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/13719/.
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Manufacturing companies must invest in new technologies and processes to succeed in a rapidly changing global environment. Managers have the difficulty of justifying capital investment in adopting new, state-of-the-art technology. Technology investment accounts for a large part of capital spending and is a key form of improving competitive advantage. Typical approaches focus on the expected return of investment and financial reward gained from the implementation of such equipment. With an increasingly dynamic market environment and global economic model, forecasting of financial payback can be argued to become increasingly less accurate. Subsequently, less quantifiable factors are becoming increasingly important. For example, the alignment of a technology with an organisations objective to fulfil future potential and gain competitive advantage is becoming as crucial as economic evaluation. In addition, the impact on human operators and skill level required must be considered. This research was motivated by the lack of decision methodologies that understand why a technology is more successful within an environment rather than re-examining the underlying performance attributes of a technology. The aim is to create a common approach where both experts and non-experts can use historical decision information to support the evaluation and selection of an optimal manufacturing technology. This form of approach is based on the logic in which a decision maker would irrationally recall previous decisions to identify relationships with new problem cases. The work investigates data mining and machine learning techniques to discover the underlying influences to improve technology selection under a set of dynamic factors. The approach initially discovers the practices to which an expert would conduct the selection of a manufacturing technology within industry. A defined understanding of the problem and techniques was subsequently concluded. This led to an understanding of the structure by which historical decision information is recalled by an expert to support new selection problems. The key attributes in the representation of a case were apparent and a form of characterising tangible and intangible variables was justified. This led to the development of a novel, experience-based manufacturing technology selection framework using fuzzy-decision-trees. The methodology is an iterative approach of learning from previously implemented technology cases. Rules and underlying knowledge of the relationships in past cases predicts the outcome of new decision problems. The link of information from a multitude of historical cases may identify those technologies with technical characteristics that perform optimally for projects with unique requirements. This also indicates the likeliness of technologies performing successfully based on the project requirements. Historical decision cases are represented through original project objectives, technical performance attributes of the chosen technology and judged project performance. The framework was shown to provide a comprehensive foundation for decision support that reduces the uncertainty and subjective influence within the selection process. The model was developed with industrial guidance to represent the actions of a manufacturing expert. The performance of the tool was measured by industrial experts. The approach was found to represent well the decision logic of a human expert based on their developed experience through cases. The application to an industrial decision case study demonstrated encouraging results and use by decision makers feasible. The model reduces the subjectivity in the process by using case information that is formed from multiple experts of a prior decision case. The model is applied in a shorter time period than existing practices and the ranking of potential solutions is well aligned to the understanding of a decision maker. To summarise, this research highlights the importance of focusing on less quantifiable factors and the performance of a technology to a specific problem/environment. The arrangement of case information thus represents the experience an expert would acquire and recall as part of the decision process.
13
Wang, Ming-hua. "A knowledge-based system approach for project management decision-making support". Thesis, University of Warwick, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340476.
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Morichetta, Andrea. "A formal approach to decision support on Mobile Cloud Computing applications". Thesis, IMT Alti Studi Lucca, 2016. http://e-theses.imtlucca.it/190/1/Morichetta_phdthesis.pdf.
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Mobile Cloud Computing (MCC) is an emergent topic growths
with the explosion of the mobile applications. In MCC systems,
application functionalities are dynamically partitioned
between the mobile devices and cloud infrastructures. The
main research direction in this field aims at optimizing different
metrics, like performance, energy efficiency, reliability
and security, in a dynamic environment in which the MCC
application is located. Optimization in MCC refers to taking
advantages from the offloading process, that consists in
moving the computation from the local device to a remote
one. The biggest challenge in this aspect is to define a strategy
that is able to decide when offloading and which part of
the application to move. This technique, in general, improves
the efficiency of a system, although sometimes it can lead to
a performance degradation.
To decide when and what to offload, in this thesis we propose
a new general framework supporting the design and the
runtime execution of applications on their own MCC scenarios.
In particular the framework provides a new specification
language, called MobiCa, equipped with a formal semantics
that permits to capture all characteristics of a MCC system.
Besides the strategy optimization achieved by exploiting the
potentiality of the model checker UPPAAL, we propose a set
of methods for determining optimal finite/infinite schedules.
They are able to manage the resource assignment of components
with the aim of improving the system efficiency in
terms of battery consumption and time. Furthermore, we
propose two optimized scheduling algorithms, developed in
Java, based on the exploitation of parallel computation in order
to improve the system performance.
15
Aiken, Milam Worth. "An expert systems approach to group decision support systems pre-session planning". Diss., The University of Arizona, 1991. http://catalog.hathitrust.org/api/volumes/oclc/31253019.html.
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Church, Lori A. "Decision support for software process management teams : an intelligent software agent approach /". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA377649.
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Thesis (M.S. in Software Engineering) Naval Postgraduate School, March 2000.Thesis advisor(s): Michael, James Bret; Osmundson, John S. "March 2000." Includes bibliographical references (p. 111-115). Also available online.
17
Zimit, Sani Ibrahim. "Hybrid approach to interpretable multiple classifier system for intelligent clinical decision support". Thesis, University of Reading, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631699.
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Data-driven decision support approaches have been increasingly employed in recent years in order to unveil useful diagnostic and prognostic patterns from data accumulated in clinical repositories. Given the diverse amount of evidence generated through everyday clinical practice and the exponential growth in the number of parameters accumulated in the data, the capability of finding purposeful task-oriented patterns from patient records is crucial for providing effective healthcare delivery. The application of classification decision support tool in clinical settings has brought about formidable challenges that require a robust system. Knowledge Discovery in Database (KDD) provides a viable solution to decipher implicit knowledge in a given context. KDD classification techniques create models of the accumulated data according to induction algorithms. Despite the availability of numerous classification techniques, the accuracy and interpretability of the decision model are fundamental in the decision processes. Multiple Classifier Systems (MCS) based on the aggregation of individual classifiers usually achieve better decision accuracy. The down size of such models is due to their black box nature. Description of the clinical concepts that influence each decision outcome is fundamental in clinical settings. To overcome this deficiency, the use of artificial data is one technique advocated by researchers to extract an interpretable classifier that mimics the MCS. In the clinical context, practical utilisation of the mimetic procedure depends on the appropriateness of the data generation method to reflect the complexities of the evidence domain. A well-defined intelligent data generation method is required to unveil associations and dependency relationships between various entities the evidence domain. This thesis has devised an Interpretable Multiple classifier system (IMC) using the KDD process as the underlying platform. The approach integrates the flexibility of MCS, the robustness of Bayesian network (BN) and the concept of mimetic classifier to build an interpretable classification system. The BN provides a robust and a clinically accepted formalism to generate synthetic data based on encoded joint relationships of the evidence space. The practical applicability of the IMC was evaluated against the conventional approach for inducing an interpretable classifier on nine clinical domain problems. Results of statistical tests substantiated that the IMC model outperforms the direct approach in terms of decision accuracy.
18
Koulouri, Anastasia. "Evaluation of a fuzzy multi-attribute value function approach to decision support". Thesis, University of Strathclyde, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415279.
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Lattanzio, Susan. "Asset Management Decision Support Tools : a conceptual approach for managing their performance". Thesis, University of Bath, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.760984.
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Decision Support Tools (DSTs) are commonly utilised within the Asset Management (AM) operations of infrastructure organisations. These manual or computerised tools are used to support decisions about what assets to acquire and how to operate them. Their performance can therefore have significant financial and non-financial implications for a business. Despite their importance, managing the performance of DSTs after implementation has received only limited attention within the literature. The output of this research is a conceptual approach for managing the performance of decision support tools used within an Asset Management context. It encompasses a risk-based DST Performance Management Process and DST Performance Assessment Techniques (the methods for applying the process in an industry setting).The novelty of the approach: (1) Alignment with the fundamental principles of the International Standard for Asset Management, ISO 5500x:2014. Thus, consistency of the management of DSTs with other assets types. (2) A generic process that is tailored to the context of the specific organisation. (3) Consistency with the risk management process (ISO 31000:2009) and meeting the requirements for a quality process defined within the Quality Management Standard (ISO 9000: 2015). (4) A cyclical process design ensuring that the approach, and how the approach is applied within an industry setting, will evolve to reflect the changing environment. A case study and the input of subject matter experts from within National Grid Electricity Transmission was used to both inform and evaluate the conceptual approach design. A semi-structured interview, with a water sector subject matter expert, assesses the transferability of the approach to a wider Asset Management population. The results of the evaluation demonstrate the conceptual approach to be both logical and useable in each context. The future research pathway looks to progress the conceptual approach through to industry adoption.
20
Leonelli, Manuele. "Bayesian decision support in complex modular systems : an algebraic and graphical approach". Thesis, University of Warwick, 2015. http://wrap.warwick.ac.uk/74066/.
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Nowadays decision centres are required to make choices in complex and evolving environments, described through multiple and interdependent processes with many associated measurements. The objective of a real time decision making centre is to agree to a sequence of efficacious countermeasures. To achieve this it is usually necessary to integrate opinions and information from an often diverse set of stakeholders, articulating several competing objectives and knowledge over different domains of expertise. A collection of decision support systems can enhance such an integration, not only ensuring that all relevant evidence systematically informs policy making, but also encouraging the decision centre to exhibit an underlying consistency across all its components and to address the problem as a whole. In this thesis we develop a formal framework, extending standard Bayesian methodology, enabling the judgements and the models of groups of experts to be coherently aggregated in a unique entity. We discuss when and how it is possible to do so and the conditions the group needs to agree upon. We call this framework integrating decision support system. We then develop a variety of methodologies to enhance such an integration, enabling integrating decision support systems to be feasibly used in practice.
21
Elmore, James Link. "Strategic Conservation Planning for High Knob, Virginia: A GIS Decision Support Approach". Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/32887.
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Conservation strategies frequently require prioritization of targets due to limited budgets and personnel. Prioritization involves choosing those areas that return the most conservation value for the time and money invested. Hence, the process of prioritization involves evaluating multiple conservation values and the uneven spatial distribution of those values across a landscape of concern. The goal of this study was to help conservation organizations improve decision making for implementation of prioritization-based strategies for land protection using a GIS-based, multi-criteria decision support system (GIS-MCDS).
Geographic Information Systems (GIS) can assist conservation planners in quantifying the relative desirability of one area over another, therefore enabling better business and ecological decisions. GIS analyses for planning are routinely undertaken over large geographic extents such as ecoregions to identify priority areas. These analyses often summarize priority by pixel values in a raster image. Implementation of conservation strategy often takes place at the much larger parcel level. Therefore, aggregating pixel-based results by parcels is a prerequisite to implementation of a purchase or easement strategy. I developed a spatial decision support system in an attempt to quantify private land holdings in the High Knob area of Virginia for their relative conservation value, as defined by the Clinch Valley Program of The Nature Conservancy. It utilizes a proxy approach for measuring conservation values and an analytical hierarchy process to aggregate the results by privately held real estate parcels.
Simple prioritizations are often based on parcel size alone, rather than consideration of the many conservation values that characterize land parcels. Though it is much quicker and easier to prioritize parcels in this manner, such simplicity risks missing important smaller areas for conservation while prioritizing larger parcels with less value. I compared this simple â bigger is betterâ ranking method to the GIS-based multi-criteria method developed for TNC. There was a 0.57 correlation between the ranked lists produced by the two models, suggesting that parcel size alone does partially explain the complexity modeled by the multi-criteria method. However, the more complex method did produce different top priority parcels, which could significantly change an organization's implementation strategy. I conclude that both methods have their applications, though the multi-criteria method is better for long-term implementations of strategic acquisition and easement.
A secondary goal was to identify to what extent land trust organizations are prepared to implement a multi-criteria type analysis like the one considered in this study. I conducted an online survey of conservation professionals on how their organization currently uses GIS and their satisfaction with GIS analyses to meet their organizational mission. Sixty-one responses were collected and analyzed. The overwhelming majority of conservation organizations recognize the benefits that GIS bring and have already developed some level of internal expertise, though many barriers to using GIS were also identified. From these results, I conclude that most land trust conservation organizations are not currently utilizing the insights that multi-criteria GIS prioritization is capable of offering, but that their previous positive experience with GIS makes such analyses an attractive proposition for those on the cutting edge of the land conservation movement.Master of Science
22
Doltsinis, Stefanos. "A decision support system for production ramp-up : a reinforcement learning approach". Thesis, University of Nottingham, 2013. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755814.
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New technologies have been developing rapidly in the last decades. Enterprises require incorporating these technologies in the development of new products. That creates a high pace of new product flow with an increasingly small life cycle. In order to support the fast pace, manufacturing lines have to adapt to the new product requirements as fast as possible. Production ramp-up is a phase in the manufacturing line that has a significant role on the required time to market but currently constitutes a bottleneck in the manufacturing process. Studies have focused on analysing ramp-up and defining its requirements to make the process more efficient. Literature shows that the key for improvement is to enhance the awareness and understanding of human operators and carry out the process more efficiently. Research studies are limited on the analysis without providing solutions on how to improve awareness. This thesis proposes an integrated approach to support decision making during production ramp-up. The work is composed of three main parts. First, a formal model is defined in order to capture the process followed on the shop floor. The model is designed as a Markov Decision Process reflecting the sequence of actions and their effect during the process. The model is composed of and defined through three main elements, namely a state space, a list of actions, and a reward formed as measure of performance during ramp-up. The second contribution of this work delves into the requirements and development of a decision support system for a more efficient ramp-up process. A decision support system is designed to operate complementary to the ramp-up process and support human operators. It captures ramp-up experience in a structured manner through a ramp-up model, processes it through a learning mechanism and communicates the extracted knowledge to human operators. The proposed system operates in two modes and supports the two identified ramp-up cases. Finally, a reinforcement learning algorithm is proposed, to extract the most effective policy for ramp-up and with a limited number of episodes. The algorithm is an outcome of a comparison study between model-based and model free algorithms. The proposed algorithm shows efficiency under the limitations of ramp-up and lack of data.
23
Kone, Alassane. "Modelling and Decision Support for a Desertification Issue Using Cellular Automata Approach". Electronic Thesis or Diss., Guyane, 2023. http://www.theses.fr/2023YANE0001.
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La désertification, en tant que problématique majeure affectant la vie sur Terre, a d’énormes conséquences qui dégradent la qualité de vie des hommes, leurs activités quotidiennes et leurs moyens de subsistance. Pour lutter contre son avancée, les organisations internationales ont mis en place des actions pour ralentir ou arrêter son expansion et réduire ses impacts.Cette thèse s’inscrit dans la lutte contre la désertification en modélisant le processus de dégradation des terres conduisant à la désertification. Deux modèles sont développés : le premier combine des automates cellulaires continus et l'évaluation MEDALUS, évaluant la désertification sur la base des indices des facteurs sol, végétation, climat et management. Le deuxième modèle simule la dégradation des terres en utilisant le couple automates cellulaires/Modèle MEDALUS, enrichi par des facteurs anthropiques comme les pratiques d'utilisation des terres, le facteur d'exploitabilité et l’appartenance foncière, formant le Modèle Amélioré de Désertification. Ce modèle sert de base au logiciel DESERTIfication Cellular Automata Software (DESERTICAS), permettant de simuler l'évolution spatio- temporelle de la dégradation des terres. DESERTICAS facilite l'exploration de scénarios de dégradation des terres dans le temps et l'espace.Ces modèles développés intègrent des processus dynamiques dans le modèle MEDALUS à la base statique et permettent d’étendre la notion d’état des automates cellulaires classiques à des états continus. L’identification d’un facteur prédominant permet d’agir sur tout le système conduisant à la désertification. Notre étude met en évidence le management, action humaine, comme facteur prédominant affectant indirectement les autres facteurs. Agir positivement sur le management permet d’interrompre les sources de dégradation, de ralentir ou arrêter la dégradation des terres. La théorie du contrôle est également appliquée au modèle d'automates cellulaires développés et permet d’agir sur le facteur prédominant à partir des algorithmes génétiques. En intégrant des actions de protection des terres dans les simulations liées à la désertification, le logiciel DESERTICAS devient un outil d'aide à la décisionDesertification, as a significant challenge impacting life on Earth, has extensive consequences that degrade human life quality, daily activities, and livelihoods. In response, international organizations have implemented actions to slow or stop its progress and reduce its impacts. This thesis focuses on combating desertification by modelling the process of land degradation leading to desertification. Two models are developed: the first combines continuous Cellular Automata and the MEDALUS assessment, evaluating desertification based on soil, vegetation, climate, and management. The second model simulates land degradation using cellular automata approach, enriched with anthropogenic factors like land use practices, exploitability factor and ownership, forming the Enhanced Model of Desertification. This model serves as the basis for DESERTIfication Cellular Automata Software (DESERTICAS), simulating spatio- temporal land degradation evolution. DESERTICAS facilitates scenario exploration by simulating land degradation progression over time and space. The models incorporate dynamic processes into the MEDALUS model, expanding classical Cellular Automata to continuous states. Identifying a predominant factor influencing desertification, management emerges as crucial, affecting other factors indirectly. Positive management actions can interrupt degradation sources, slowing or halting land degradation. The thesis also applies control theory to the Cellular Automata model, aiming to influence the predominant factor using Genetic Algorithms. By integrating land protection actions into desertification simulations, the DESERTICAS software becomes a decision support tool
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Alden, James G. Hopeman Amber L. Neff Jodi A. "Transforming change in the military a systems approach /". Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Jun%5FAlden.pdf.
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Thesis (M.S. in Defense Analysis)--Naval Postgraduate School, June 2007.Thesis Advisor(s): Erik Jansen, George Lober. "June 2007." Includes bibliographical references (p. 73-81). Also available in print.
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Kong, Guilan. "An online belief rule-based group clinical decision support system". Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/an-online-belief-rulebased-group-clinical-decision-support-system(c31a65c7-60c3-4e7a-b18e-44fee95f7da1).html.
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Around ten percent of patients admitted to National Health Service (NHS) hospitals have experienced a patient safety incident, and an important reason for the high rate of patient safety incidents is medical errors. Research shows that appropriate increase in the use of clinical decision support systems (CDSSs) could help to reduce medical errors and result in substantial improvement in patient safety. However several barriers continue to impede the effective implementation of CDSSs in clinical settings, among which representation of and reasoning about medical knowledge particularly under uncertainty are areas that require refined methodologies and techniques. Particularly, the knowledge base in a CDSS needs to be updated automatically based on accumulated clinical cases to provide evidence-based clinical decision support. In the research, we employed the recently developed belief Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER) for design and development of an online belief rule-based group CDSS prototype. In the system, belief rule base (BRB) was used to model uncertain clinical domain knowledge, the evidential reasoning (ER) approach was employed to build inference engine, a BRB training module was developed for learning the BRB through accumulated clinical cases, and an online discussion forum together with an ER-based group preferences aggregation tool were developed for providing online clinical group decision support.We used a set of simulated patients in cardiac chest pain provided by our research collaborators in Manchester Royal Infirmary to validate the developed online belief rule-based CDSS prototype. The results show that the prototype can provide reliable diagnosis recommendations and the diagnostic performance of the system can be improved significantly after training BRB using accumulated clinical cases.
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Rupakheti, Sanjib. "Evaluation of Rural Sanitation Alternatives in Nepal Using Decision Support System (DSS) Approach". Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-200181.
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A society´s health depends on the access to proper and hygiene sanitation. Half of the population still do not have access to proper sanitation in Nepal; therefore government and non-government organizations are facilitating sanitation access to all the population. Decades ago, open defecation and pit latrines toilet were the only options as sanitation system to the people. But now, various types of toilets system known as dry toilets, septic tanks, centralized sewerage system and biogas integrated toilets are available. Therefore, existing toilet system in rural areas of Nepal needs to be evaluated with respect to environment and long term sustainability. Aim of this study is to find the appropriate toilet system for rural areas of Nepal. This study also discusses how that appropriate toilet system can be promoted based on current scenarios from government level to local level. Generic Multi-Attribute Analysis (GMAA) is used as a decision support tools to evaluate available various toilet alternatives. For which a rural area from Nepal is chosen as study area. GMAA helps in evaluating all the toilet system based on social, technological, environmental and economical aspects. Interpretation between the toilet systems can be made easily with the help of GMAA results. Field questionnaire survey was also carried out in the study area to know user´s understanding of toilet alternatives. Every toilet systems have pro and cons based on different social, technological, environmental and economical aspects. It was found that pit latrines toilet systems are mostly practiced in the rural areas of Nepal. User prefers pit latrines because of its social accepted character and technologically easy in using it. Biogas integrated toilet system came as optimal toilet system though not accessible to all household. It was found that urine and faeces separating toilets are environmentally and economically beneficial. The thesis concludes that appropriate toilet system which is sustainable must be promoted while increasing toilet coverage in Nepal. Urine and faeces separating toilet is found to be appropriate and need to be incorporated in the government goal of increasing toilet coverage.
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Novelli, Emanuele [Verfasser]. "A Rapid Impact Assessment Approach for Decision Support in Food Policy / Emanuele Novelli". Bonn : Universitäts- und Landesbibliothek Bonn, 2012. http://d-nb.info/1043054693/34.
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Tuot, Christopher [Verfasser]. "A Collaborative Knowledge Management Approach to Provide Better Agricultural Decision Support / Christopher Tuot". München : Verlag Dr. Hut, 2012. http://d-nb.info/1022535420/34.
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Erharuyi, Nosakhare. "A task level adaptation approach in mobile GIS for disaster response decision support". Thesis, University of Newcastle Upon Tyne, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424335.
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DIZ, GUSTAVO SOUTO DOS SANTOS. "AN OPTIMIZATION BASED DECISION SUPPORT SYSTEM PROPOSED FOR SHIP SCHEDULING: A PRACTICAL APPROACH". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=20764@1.
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O aumento da produção de petróleo brasileiro e o consequente aumento na
demanda por transporte marítimo levaram a PETROBRAS a buscar ferramentas
para aumentar a eficiência de seu transporte marítimo. Neste sentido, a atividade
de programação de navios busca alocar os navios a um conjunto de cargas
definido a priori, respeitando as restrições comerciais e operacionais, a fim de
transportá-las com o menor custo possível. Com o intuito de auxiliar o
programador nesta atividade, esta dissertação propõe um sistema de suporte à
decisão (SSD) baseado em otimização para a programação de navios. O SSD
proposto foi desenhado especificamente para a atividade de longo curso de navios
de petróleo da PETROBRAS, sendo este gerado a partir da adaptação de modelos
disponíveis na literatura acadêmica. Os testes comparativos realizados com o
protótipo do SSD na atividade de longo curso de navios de petróleo mostraram
que a ferramenta tem um significativo potencial de redução de custo. O SSD
proposto se apresentou como uma opção viável para auxiliar a programação de
navios da companhia na busca pela redução de custos de transporte marítimo.The increasing production of Brazilian oil and the consequent increase in the demand for shipping, led PETROBRAS to seek tools to increase the efficiency of its shipping. In this sense, the activity of ship scheduling seeks to assign vessels to a set of cargos, respecting business and operational restrictions in order to transport them with the lowest possible cost. To assist the ship scheduling planner in this activity, this dissertation proposes an optimization based decision support system (DSS) for ship scheduling. The proposed DSS was designed specifically for the long-term tanker scheduling activity at PETROBRAS and it was implemented based on models available in the academic literature. The comparative tests using the DSS prototype proposed in this dissertation showed that it has a potential for significant cost reduction. The proposed DSS was considered a viable tool to assist the ship scheduling planners in reducing shipping costs.
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Marhamati, Nina. "Integration of Bayesian Decision Theory and Computing with Words: A Novel Approach to Decision Support Using Z-numbers". OpenSIUC, 2016. https://opensiuc.lib.siu.edu/dissertations/1279.
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Decision support systems have emerged over five decades ago to serve decision makers in uncertain conditions and usually rapidly changing and unstructured problems. Most decision support approaches, such as Bayesian decision theory and computing with words, compare and analyze the consequences of different decision alternatives. Bayesian decision methods use probabilities to handle uncertainty and have been widely used in different areas for estimating, predicting, and offering decision supports. On the other hand, computing with words (CW) and approximate reasoning apply fuzzy set theory to deal with imprecise measurements and inexact information and are most concerned with propositions stated in natural language. The concept of a Z-number [69] has been recently introduced to represent propositions and their reliability in natural language. This work proposes a methodology that integrates Z-numbers and Bayesian decision theory to provide decision support when precise measurements and exact values of parameters and probabilities are not available. The relationships and computing methods required for such integration are derived and mathematically proved. The proposed hybrid methodology benefits from both approaches and combines them to model the expert knowledge and its certainty (reliability) in natural language and apply such model to provide decision support. To the best of our knowledge, so far there has been no other decision support methodology capable of using the reliability of propositions in natural language. In order to demonstrate the proof of concept, the proposed methodology has been applied to a realistic case study on breast cancer diagnosis and a daily life example of choosing means of transportation.
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Mikkelsen, Joar Hylland. "Decision support from monitoring of hydro power stations : An approach to the vision of monitoring systems giving decision support in operation of hydro power stations". Thesis, Norwegian University of Science and Technology, Department of Electrical Power Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9910.
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This report is the results of the work on a master thesis concerning intelligent monitoring of hydro power stations. In the report two different types of computer software is investigated to find out whether they are suitable to make out a monitoring system capable of giving the user information about faults and unwanted operating conditions at an early stage. It is also investigated whether the software has proven the capability to detect faults and unwanted operating conditions. The different advantages and disadvantages of the two software products are commented and the two software products are compared. This report shows that the two software products are quite different. The software from Volve is software meant to construct an expert system capable of recognising faults from previous cases of faults. The software from SKF is software that gives intelligent machine diagnostics from analysis of vibration measurements in addition to measuring and trending of other variables. It also gives the user tools for analysing the root cause of faults influencing the bearing system of different industry machinery. This means that the software from SKF demands some involvement from the user to produce the best and most precise results. The expert system developed from the Volve software on the other hand is meant to present only results and advice to the user. The results from tests and simulations of the expert system developed by the Volve software are very limited. It is not possible to conclude which of the two software products is better before more tests of the Volve system is performed. In addition to the investigation of these two monitoring software products two different types of sensors are investigated. The sensors that are investigated are smoke sensors and sensors for detection of ultrasonic sound. Both types are commonly used in monitoring of industry processes similar to those in hydro power stations. These two sensors are capable of giving additional information to the monitoring system making it possible to detect faults that it is difficult to detect today. This is because the two sensor types perform measurements that the normal measuring equipment of today is incapable of. This will increase the information flow to the monitoring systems of hydro power stations making it possible to perform better and more precise monitoring.
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Ismail, Ashraf Lotfy R. M. "The 3D-CAD modelling paradigm : a pragmatic approach to conceptual design evaluation and modelling support". Thesis, University of Portsmouth, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309570.
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Hampshire, Philip. "The development of an approach and decision support tool to inform sustainable roof selection". Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.681042.
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Despite the importance of roofs, improved roof selection has not been explored in significant depth. Therefore this research explores the possibilities that roofs offer to improve the value and sustainability of buildings. It is concerned with the roof as a system, explicitly connected with the building and their impacts on wider society. This research, develops and tests techniques to better understand what constitutes value and sustainability for a building project’s context through action research. The sustainability and value themes output through the use of such techniques are then considered as a basis for the selection of roof attributes through Keeney’s value focused thinking approach. Once the roof performance attributes have been established, designers and clients then require quantitative data to decide which roof type represents the highest value / most sustainable option. Thus the research also collates and maps peer reviewed quantitative performance data on the performance of roofing systems in relation to climate type as well as providing information from leading modelling packages for different roof options. An approach for selecting the most appropriate data is then developed. This allows the practitioner to be able to access reliable peer reviewed information and utilise leading modelling techniques to quickly gain information regarding the performance of various roof systems for use in the project context. An approach is developed to bring this information together with the important sustainability considerations for the project to inform sustainable roof selection. This combines the different types of roof performance with the relevant decision attributes early in the design process, to provide insight into which roof option represents the best overall economic, environmental and social value and therefore the most sustainable roof option. The primary contribution to knowledge presented in this thesis is the development of a pragmatic realist approach to sustainable roof selection.
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Guedes, A. P. "An integrated approach to logistics strategy planning using visual interactive modelling and decision support". Thesis, Cranfield University, 1994. http://dspace.lib.cranfield.ac.uk/handle/1826/10740.
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The research in this thesis relates to the use of mathematical models and ièigputer-based
modelling tools for supporting the Logistics Strategy Planning (LSP) process. conceptual
modelling framework and a computer-based modelling and decision support system are
developed to address practical LSP problems and improve the level of decision support currently
reported.
A LSP process
T
is described, its
h
complexity recognised,
e
and the problem domain defined. The
evolution of the logistics strategy concept is addressed and defined a integrating procurement,
production and distribution aspects. The need for decision support is also identified.
A
comprehensive review of models and modelling techniques from Management Science /
Operations Research (MS/OR), and computer based tools in the LSP context is carried out. The
appropriateness of the various models and types of computer tools is assessed. Gaps and
drawbacks in current approaches to LSP are also identified. This revealed that past efforts have
been directed towards producing more efficient solving techniques and tools for limited aspects
of LSP, rather than developing models and tools that could address more realistic problems,
recognising a integrated view of LSP. Hence, current approaches to LSP are fragmented in their
handling of the procurement, production and distribution aspects.
A
conceptual modelling framework is proposed to support the LSP process. It includes a
planning process, the logistics elements and key drivers required to define a model/representation
of the LSP problem, and a selection of models/techniques to address various classes of LSP
(sub-) problems. The framework provides a integrated view of all elements involved and
contributes to formalise the knowledge necessary to address LSP problems.
A
modelling and decision support system is developed in order to demonstrate the framework
and assess the approach here proposed to address practical LSP studies. STRATOVISION
combines Visual Interactive Modelling (VIM) and Knowledge-Based (KB) techniques with
"traditional" MS/OR models and modelling techniques. Additionally, the system implements a
problem centred approach, combining various MS/OR solving techniques (e.g. simulation,
heuristics and optimisation) into a unique modelling environment.
A
comparative analysis and discussion of functionality supports the view that STRATOVISION
overcomes most limitations found with other modelling systems and provides better functionality
to address LSP problems. The discussion covers the modelling phase, the options generation and
the detailed evaluation of scenarios. Special emphasis is given both to the use of the Visual
Interactive ( I) functionality for modelling and problem solving, and to the use of
models/techniques included in STRATOVISION's model base.
Several case studies are used to illustrate STRATOVISION's integrated approach to LSP and
validate the model design. Comparison with fragmented approaches to LSP is carried out and
the use of STRATOVISION in practical LSP studies including procurement, production and
distribution decisions is reported. The analysis provides supporting evidence of the benefits
achieved by using STRATOVISION's integrated approach to LSP.
Finally, contributions of the approach are discussed and areas of further work pointed out.
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Azhar, Salman. "Information systems to support decision-making in construction owner organizations : a data warehousing approach". FIU Digital Commons, 2005. http://digitalcommons.fiu.edu/etd/1356.
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Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making.
A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework.
One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.
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Liu, Dingfei. "An object-oriented approach to structuring multicriteria decision support in natural resource management problems". Doctoral thesis, University of Cape Town, 2001. http://hdl.handle.net/11427/4384.
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Includes bibliographical references.The undertaking of MCDM (Multicriteria Decision Making) and the development of DSSs (Decision Support Systems) tend to be complex and inefficient, leading to low productivity in decision analysis and DSSs. Towards this end, this study has developed an approach based on object orientation for MCDM and DSS modelling, with the emphasis on natural resource management. The object-oriented approach provides a philosophy to model decision analysis and DSSs in a uniform way, as shown by the diagrams presented in this study. The solving of natural resource management decision problems, the MCDM decision making procedure and decision making activities are modelled in an object-oriented way. The macro decision analysis system, its DSS, the decision problem, the decision context, and the entities in the decision making procedure are represented as "objects". The object-oriented representation of decision analysis also constitutes the basis for the analysis ofDSSs.
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Zhu, Xuan. "A knowledge-based approach to the design and implementation of spatial decision support systems". Thesis, University of Edinburgh, 1995. http://hdl.handle.net/1842/21632.
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Geographical information systems (GIS), expert systems (ES) and spatial decision support systems (SDSS) are becoming important tools for supporting managers and planners in making decisions for resource and environmental management. In recent years, attention has turned to the integration of existing GIS, ES systems and other problem-solving techniques to develop more powerful SDSS systems. Such systems should lead to significant competitive advantages, such as cost savings, the ability to couple analytical modelling with heuristic reasoning, and automated explanation facilities for interpreting and justifying the results of modelling studies. However, early attempts have also demonstrated a number of drawbacks, such as user unfriendliness, lack of flexible model management capabilities and poor adaptation to users' needs. To try and overcome some of these problems, this research establishes a new approach to the development of spatial decision support systems within an integrated framework of GIS, spatial modelling and expert systems techniques and technologies. In this approach, knowledge-based techniques are introduced into the design of knowledge-based spatial decision support systems (KBSDSS), with emphasis on the design of a representation scheme based on spatial influence diagrams and mechanisms for structuring, representing and formulating spatial problems, together with automation of the solution process. Spatial influence diagrams are graphic knowledge representations for resource and environmental problems, consisting of information about all problem variables or parameters and their relationships. They can be seen as spatial analogues of influence diagrams developed for decision analysis. However, spatial influence diagrams are deterministic cases of influence diagrams without decision components. Algorithms are developed to formulate and evaluate spatial influence diagrams using domain-specific knowledge in the system to represent and evaluate specific spatial problems according to the decision marker's perspective.
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CLEMENTE, MONICA. "Decision Support System Approach for the Management of Complex Systems in Transportation and Logistics". Doctoral thesis, Università degli Studi di Trieste, 2016. http://hdl.handle.net/11368/2908080.
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L'analisi e la gestione dei sistemi complessi e delle loro ripercussioni in diversi aspetti della vita quotidiana sono tematiche che continuano ad attrarre molta attenzione nella letteratura scientifica.
Si considerino, ad esempio, il trasporto marittimo e su strada, i moderni sistemi di assistenza sanitaria, le catene di distribuzione integrate, i processi industriali o, ancora, il nuovo paradigma di città intelligente: è evidente come in tutti questi contesti vi sia sempre più la necessità di analizzare e gestire elementi eterogenei, collegati tra loro al fine di raggiungere un obiettivo comune altrimenti non realizzabile. Tuttavia, il processo decisionale in tali ambiti richiede competenze trasversali che abbracciano svariate discipline, rendendo la gestione di questi sistemi molto complessa e, spesso, inefficace.
I Sistemi di Supporto alle Decisioni (DSS) ben si adattano alla previsione ed al controllo dei sistemi complessi grazie a: la loro capacità di integrare varie fonti di dati ed informazioni; l'applicazione di modelli formali tipici di diverse discipline; la possibilità di interagire costantemente con il sistema considerato.
L'obiettivo di questo lavoro di tesi è quello di definire un approccio generale basato sul concetto di DSS per la gestione di sistemi complessi nel settore dei trasporti e della logistica, e di applicare tale approccio a tre problemi di grande interesse oggigiorno: 1) il problema della ricollocazione dei veicoli nei servizi di car sharing, 2) la gestione intelligente delle operazioni di carica dei veicoli elettrici presso le infrastrutture pubbliche e 3) l'ottimizzazione delle operazioni di drayage nel trasporto container. In particolare, il focus della ricerca è rivolto al cuore del DSS, ovvero alla parte che direttamente supporta il processo decisionale: i moduli di ottimizzazione e simulazione e le loro interazioni. Vengono considerati diversi approcci di modellazione, simulazione ed ottimizzazione, evidenziando il carattere totalmente generale dell' approccio considerato.
I risultati ottenuti nelle diverse applicazioni sottolineano l'efficacia dei DSS nel migliorare il processo decisionale, portando ad un miglioramento generale delle prestazioni dei sistemi in esame. In particolare: 1) l'applicazione del DSS permette di ottimizzare i set-point per l'introduzione di un sistema di incentivi economici atto a risolvere il problema di ricollocazione dei veicoli nei servizi di car sharing, garantendo un miglioramento delle prestazioni del sistema, anche in condizioni di quasi saturazione; 2) il DSS permette la formalizzazione di un approccio leader-follower per il coordinamento delle operazioni di ricarica di veicoli elettrici che tenga conto contemporaneamente sia dei requisiti dell'utente che quelli della rete elettrica; infine, 3) il DSS consente di migliorare l'efficienza delle operazioni di drayage nel trasporto containter, riducendo i costi di trasporto.In recent years, the analysis and management of complex systems and their impacts in many aspects of the every-day life are topics that attract a lot of attention in the scientific literature. Consider for instance road and maritime transportation, modern healthcare systems, integrated supply chains, industrial processes or the new paradigm of smart cities: it is apparent that in all these contexts there is an increasing need of analysing and managing heterogeneous elements, networked together in order to reach a common goal otherwise not achievable. However, making decisions concerning such systems requires specific competences from many disciplines, leading to a very complex and often ineffective management process. Decision Support Systems (DSSs) can strengthen the capacity of predicting and controlling complex systems by integrating various sources of data and information, applying formal models typical of diverse and isolated disciplines and constantly interacting with the considered system. The goal of this work is to define a general approach based on the DSS concept for the management of complex systems in transportation and logistics and to apply it to three problems of great interest nowadays: 1) the user-based vehicle relocation problem} in car sharing services, 2) the smart management of electric vehicles charging operations and 3) the container drayage problem. In particular, the focus of the research is on the core of the DSS, i.e., on the part that directly supports the decision making process: optimization modules, simulation modules and their interactions. Different modelling, simulation and optimization approaches are applied, highlighting the generality of the considered approach regardless the specific context analysed. Results show the ability of DSSs to enhance the effectiveness of the decision process, thus leading to an improvement of the considered systems performance. In particular: 1) the application of the DSS allows to optimize the set-points of an incentive policy designed to solve the vehicle relocation problem in car sharing services, guaranteeing an effective relocation and improving the system performance even in the case of nearly saturated offer; 2) the DSS allows the formalization of a leader-follower approach for the coordination of electric vehicles charging operations which takes into account simultaneously electric grid and drivers requirements; finally, 3) the DSS allows to improve the efficiency of drayage operations in container transportation, reducing total transportation costs.
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Lin, Frank Ching-Shou. "The integration between design and maintenance of office building automation : a decision support approach". Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16058/1/Frank_Lin_Thesis.pdf.
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This research explores the barriers and limitations of the interaction between building development processes in an attempt of an integrated decision support approach to improve building design for effective maintenance in the field of office building automation.
Extensive coverage of literature and practice in office building industry over the last two decades indicates a wide diffusion and application of the information and communication technologies (ICT). While this has resulted in the adoption of advanced system integration in buildings, system redundancy and excessive expenditures are causing a major impact on the overall efficiency and has burdened building owners and occupiers with escalating maintenance costs. This phenomenon stimulates and warrants the re-examination of integrated building development, not just on system integration but also on the interdisciplinary development process integration particularly linking design and maintenance.
Studies in this field revealed existing problems such as the inherent professional fragmentation, lack of historical information and service data, the first cost mentality of owners and developers, difficulties in forecasting future conditions and changes early in the design stage. With extensive use of qualitative information, this situation presents a great potential for the development of a decision support system exploring the communication and integration of design and maintenance phases, which has been one of the primary objectives of this research.
In addition to literature studies, a questionnaire survey and a case study to identify industry concerns, feasible solutions, and practical procedure oriented approaches through knowledge extractions were carried out. A set of guidelines, a checklist for its implementation and prototype system for computerized decision support to design and maintenance of building automation systems were also produced. These strategic approaches to balance design and maintenance will help facilitate appropriate decision making in the early design stage for sustainable maintenance of buildings.
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Lin, Frank Ching-Shou. "The integration between design and maintenance of office building automation : a decision support approach". Queensland University of Technology, 2005. http://eprints.qut.edu.au/16058/.
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This research explores the barriers and limitations of the interaction between building development processes in an attempt of an integrated decision support approach to improve building design for effective maintenance in the field of office building automation.
Extensive coverage of literature and practice in office building industry over the last two decades indicates a wide diffusion and application of the information and communication technologies (ICT). While this has resulted in the adoption of advanced system integration in buildings, system redundancy and excessive expenditures are causing a major impact on the overall efficiency and has burdened building owners and occupiers with escalating maintenance costs. This phenomenon stimulates and warrants the re-examination of integrated building development, not just on system integration but also on the interdisciplinary development process integration particularly linking design and maintenance.
Studies in this field revealed existing problems such as the inherent professional fragmentation, lack of historical information and service data, the first cost mentality of owners and developers, difficulties in forecasting future conditions and changes early in the design stage. With extensive use of qualitative information, this situation presents a great potential for the development of a decision support system exploring the communication and integration of design and maintenance phases, which has been one of the primary objectives of this research.
In addition to literature studies, a questionnaire survey and a case study to identify industry concerns, feasible solutions, and practical procedure oriented approaches through knowledge extractions were carried out. A set of guidelines, a checklist for its implementation and prototype system for computerized decision support to design and maintenance of building automation systems were also produced. These strategic approaches to balance design and maintenance will help facilitate appropriate decision making in the early design stage for sustainable maintenance of buildings.
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Das, Swarup. "An Approach towards design of a GIS anchored decision support system for tea management". Thesis, University of North Bengal, 2007. http://hdl.handle.net/123456789/18.
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Hernandez, Gabriel. "A probabilistic-based design approach with game theoretical representations of the enterprise design process". Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/33422.
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Silva, Frederica Nishakumari de. "CEMPS - spatial decision support system for evacuation planning : an operational research - geographical information systems approach". Thesis, Lancaster University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242839.
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Azuaje, Francisco Javier. "An unsupervised neural learning approach to retrieval strategies for case-based reasoning and decision support". Thesis, University of Ulster, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311877.
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Rodríguez, Loya Salvador. "A standards-based ICT framework to enable a service-oriented approach to clinical decision support". Thesis, University of Sussex, 2015. http://sro.sussex.ac.uk/id/eprint/53243/.
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This research provides evidence that standards based Clinical Decision Support (CDS) at the point of care is an essential ingredient of electronic healthcare service delivery. A Service Oriented Architecture (SOA) based solution is explored, that serves as a task management system to coordinate complex distributed and disparate IT systems, processes and resources (human and computer) to provide standards based CDS. This research offers a solution to the challenges in implementing computerised CDS such as integration with heterogeneous legacy systems. Reuse of components and services to reduce costs and save time. The benefits of a sharable CDS service that can be reused by different healthcare practitioners to provide collaborative patient care is demonstrated. This solution provides orchestration among different services by extracting data from sources like patient databases, clinical knowledge bases and evidence-based clinical guidelines (CGs) in order to facilitate multiple CDS requests coming from different healthcare settings. This architecture aims to aid users at different levels of Healthcare Delivery Organizations (HCOs) to maintain a CDS repository, along with monitoring and managing services, thus enabling transparency. The research employs the Design Science research methodology (DSRM) combined with The Open Group Architecture Framework (TOGAF), an open source group initiative for Enterprise Architecture Framework (EAF). DSRM's iterative capability addresses the rapidly evolving nature of workflows in healthcare. This SOA based solution uses standards-based open source technologies and platforms, the latest healthcare standards by HL7 and OMG, Decision Support Service (DSS) and Retrieve, Update Locate Service (RLUS) standard. Combining business process management (BPM) technologies, business rules with SOA ensures the HCO's capability to manage its processes. This architectural solution is evaluated by successfully implementing evidence based CGs at the point of care in areas such as; a) Diagnostics (Chronic Obstructive Disease), b) Urgent Referral (Lung Cancer), c) Genome testing and integration with CDS in screening (Lynch's syndrome). In addition to medical care, the CDS solution can benefit organizational processes for collaborative care delivery by connecting patients, physicians and other associated members. This framework facilitates integration of different types of CDS ideal for the different healthcare processes, enabling sharable CDS capabilities within and across organizations.
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Dimitrova, V., M. O. Mehmood, Dhaval Thakker, B. Sage-Vallier, J. Valdes e A. G. Cohn. "An ontological approach for pathology assessment and diagnosis of tunnels". ELSEVIER, 2019. http://hdl.handle.net/10454/17643.
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YesTunnel maintenance requires complex decision making, which involves pathology diagnosis and risk assessment, to ensure full safety while optimising maintenance and repair costs. A Decision Support System (DSS) can play a key role in this process by supporting the decision makers in identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key aspect is to identify which spatial stretches within a tunnel contain pathologies of similar kinds within neighbouring tunnel segments. This paper presents PADTUN, a novel intelligent decision support system that assists with pathology diagnosis and assessment of tunnels with respect to their disorders and diagnosis influencing factors. It utilises semantic web technologies for knowledge capture, representation, and reasoning. The core of PADTUN is a family of ontologies which represent the main concepts and relations associated with pathology assessment, and capture the decision process concerning tunnel maintenance. Tunnel inspection data is linked to these ontologies to take advantage of inference capabilities offered by semantic technologies. In addition, an intelligent mechanism is presented which exploits abstraction and inference capabilities. Thus PADTUN provides the world’s first semantically based intelligent DSS for tunnel maintenance. PADTUN was developed by an interdisciplinary team of tunnel experts and knowledge engineers in real-world settings offered by the NeTTUN EU Project. An evaluation of the PADTUN system is performed using real-world tunnel data and diagnosis tasks. We show how the use of semantic technologies allows addressing the complex issues of tunnel pathology inferencing, aiding in, and matching transportation experts’ expectations of decision support. The methodology is applicable to any linear transport structures, offering intelligent ways to aid with complex decision processes related to diagnosis and maintenance.
This work was part of the NeTTUN project, funded by the EC 7th Framework under Grant Agreement 280712.
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Omar, Mohd Faizal. "The structured and practical approach in development of decision support system for consultant selection in public sector infrastructure project". Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/64458/1/Mohd_Omar_Thesis.pdf.
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Nowadays, most of the infrastructure development projects undertaken are complex in nature. Practically, public clients who do not have a good understanding of the design and management may suffer severe losses, especially for infrastructure projects. There is a need for luring the right consultant to secure client's investment in infrastructure developments. Throughout the project life cycle, consultants play vital role from the inception to completion stage of a project. A few studies in Malaysia show that infrastructure projects involving irrigation and drainage have experience problems such as poor workmanship, delay and cost overrun due to the consultant's inability or the client incompetence of recruiting consultants in time. This highlights the need of aided decision making and an efficient system to select the best consultant by using Decision Support System (DSS). On the other hand, recent trends reveal that most DSS in construction only concentrate on decision model development. These models are impractical and unused as they are complicated or difficult for laymen such as project managers to utilize. Thus, this research attempts to develop an efficient DSS for consultant selection namely consultDeSS.
Driven by the motivation and research aims, this study deployed Design Science Research Methodology (DSRM) dominant with a combination of case studies at the Malaysian Department of Irrigation and Drainage (DID). Two real projects involving irrigation and drainage infrastructure were used to design, implement and evaluate the artefact. The 3-tier consultDeSS was revised after the evaluation and the design was significantly improved based on user feedback.
By developing desirable tools that fit client's needs will enhance the productivity and minimize conflict within groups and organisations. The tool is more usable and efficient compared to previous studies in construction. Thus, this research has demonstrated a purposeful artefact with a practical and valid structured development approach that is applicable in a variety of problems in construction discipline.
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Subagadis, Yohannes Hagos. "A new integrated modeling approach to support management decisions of water resources systems under multiple uncertainties". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-189212.
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The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational framework. Such integrative research to link different knowledge domains faces several practical challenges. The complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions.
This thesis aims to overcome some of these challenges, and to demonstrate how new modeling approaches can provide successful integrative water resources research. It focuses on the development of new integrated modeling approaches which allow integration of not only physical processes but also socio-economic and environmental issues and uncertainties inherent in water resources systems. To achieve this goal, two new approaches are developed in this thesis.
At first, a Bayesian network (BN)-based decision support tool is developed to conceptualize hydrological and socio-economic interaction for supporting management decisions of coupled groundwater-agricultural systems. The method demonstrates the value of combining different commonly used integrated modeling approaches. Coupled component models are applied to simulate the nonlinearity and feedbacks of strongly interacting groundwater-agricultural hydrosystems. Afterwards, a BN is used to integrate the coupled component model results with empirical knowledge and stakeholder inputs.
In the second part of this thesis, a fuzzy-stochastic multiple criteria decision analysis tool is developed to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrates physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework.
Subsequently, the proposed new approaches are applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structures.
The results show the effectiveness of the proposed methods. The first method can aid in the impact assessment of alternative management interventions on sustainability of aquifer systems while accounting for economic (agriculture) and societal interests (employment in agricultural sector) in the study area. Results from the second method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach suits to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. The new approaches can be applied to address the complexities and uncertainties inherent in water resource systems to support management decisions, while serving as a platform for stakeholder participation.
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Sumic, Zarko. "The concept and feasibility of automated electrical plat design via an intelligent decision support system approach /". Thesis, Connect to this title online; UW restricted, 1990. http://hdl.handle.net/1773/5885.
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