Relevant bibliographies by topics / Multiple criteria analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Multiple criteria analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 May 2022

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Journal articles on the topic "Multiple criteria analysis"

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Nuthall, P. L. "MULTIPLE CRITERIA ANALYSIS." Agricultural Economics 5, no. 2 (June 1991): 174–78. http://dx.doi.org/10.1111/j.1574-0862.1991.tb00147.x.

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Flores, Benito E., and D. Clay Whybark. "Multiple Criteria ABC Analysis." International Journal of Operations & Production Management 6, no. 3 (March 1986): 38–46. http://dx.doi.org/10.1108/eb054765.

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Antoine, Jacques, Günther Fischer, and Marek Makowski. "Multiple criteria land use analysis." Applied Mathematics and Computation 83, no. 2-3 (May 1997): 195–215. http://dx.doi.org/10.1016/s0096-3003(96)00190-7.

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Zavadskas, E. K., A. Kaklauskas, N. Lepkova, and J. Zalatorius. "FACILITIES MANAGEMENT MULTIPLE CRITERIA ANALYSIS." Statyba 7, no. 6 (January 2001): 481–89. http://dx.doi.org/10.1080/13921525.2001.10531776.

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Flores, Benito E., and D. Clay Whybark. "Implementing multiple criteria ABC analysis." Engineering Costs and Production Economics 15 (May 1989): 191–95. http://dx.doi.org/10.1016/0167-188x(89)90124-9.

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Flores, Benito E., and D. Clay Whybark. "Implementing multiple criteria ABC analysis." Journal of Operations Management 7, no. 1-2 (October 1987): 79–85. http://dx.doi.org/10.1016/0272-6963(87)90008-8.

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Nijkamp, Peter. "MULTIPLE CRITERIA ANALYSIS AND INTEGRATED IMPACT ANALYSIS." Impact Assessment 4, no. 3-4 (March 1986): 226–61. http://dx.doi.org/10.1080/07349165.1986.9725786.

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Nijkamp, Peter, Hans Schaffers, and Jaap Spronk. "Multiple futures and multiple discount rates in multiple criteria analysis." Project Appraisal 4, no. 1 (March 1989): 2–8. http://dx.doi.org/10.1080/02688867.1989.9726699.

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Kaftanowicz, Michał, and Michał Krzemiński. "Multiple-criteria Analysis of Plasterboard Systems." Procedia Engineering 111 (2015): 364–70. http://dx.doi.org/10.1016/j.proeng.2015.07.102.

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Greene, Randal, Rodolphe Devillers, Joan E. Luther, and Brian G. Eddy. "GIS-Based Multiple-Criteria Decision Analysis." Geography Compass 5, no. 6 (June 2011): 412–32. http://dx.doi.org/10.1111/j.1749-8198.2011.00431.x.

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Dissertations / Theses on the topic "Multiple criteria analysis"

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Chen, Ye. "Multiple Criteria Decision Analysis: Classification Problems and Solutions." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2892.

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Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are
  1. Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice.
  2. Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively.
  3. Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM.
Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example.

Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components.

A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem.
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Sobrie, Olivier. "Learning preferences with multiple-criteria models." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC057/document.

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L’aide multicritère à la décision (AMCD) vise à faciliter et améliorer la qualité du processus de prise de décision. Les méthodes d’AMCD permettent de traiter les problèmes de choix, rangement et classification. Ces méthodes impliquent généralement la construction d’un modèle. Déterminer les valeurs des paramètres de ces modèles n’est pas aisé. Les méthodes d’apprentissage indirectes permettent de simplifier cette tâche en apprenant les paramètres du modèle de décision à partir de jugements émis par un décideur tels que “l’alternative a est préférée à l’alternative b” ou “l’alternative a doit être classifiée dans la meilleure catégorie”. Les informations données par le décideur sont généralement parcimonieuses. Le modèle d’AMCD est appris au cours d’un processus interactif entre le décideur et l’analyste. L’analyste aide le décideur à formuler et revoir ses jugements si nécessaire. Le processus s’arrête une fois qu’un modèle satisfaisant les préférences du décideur a été trouvé. Le “preference learning” (PL) est un sous domaine du “machine learning” qui s’intéresse à l’apprentissage des préférences. Les algorithmes de ce domaine sont capables de traiter de grands jeux de données et sont validés au moyen de jeux de données artificiels et réels. Les jeux de données traités en PL sont généralement collectés de différentes sources et sont entachés de bruit.Contrairement à l’AMCD, il existe peu ou pas d’interaction avec l’utilisateur en PL. Le jeu de données fourni en entrée à l’algorithme est considéré comme un échantillon éventuellement bruité d’une “réalité” ou “vérité de terrain”. Les algorithmes utilisés dans ce domaine ont des propriétés statistiques fortes leur permettant de s’affranchir du bruit dans ces jeux de données. Dans cette thèse, nous développons des algorithmes d’apprentissage permettant d’apprendre lesparamètres de modèles d’AMCD. Plus précisément, nous développons une métaheuristique afin d’apprendre les paramètres d’un modèle appelé MR-Sort (“majority rule sorting”). Cette métaheuristique est testée sur des jeux de donnéesartificiels et réels utilisés dans le domaine du PL. Nous utilisons cet algorithme afin de traiter un problème concret dans le domaine médical. Ensuite nous modifions la métaheuristique afin d’apprendre les paramètres d’un modèle plus expressif appelé NCS (“non-compensatory sorting”). Finalement, nous développons un nouveau type de règle de veto pour les modèles MR-Sort et NCS qui permet de prendre les coalitions de critères en compte. La dernière partie de la thèse introduit les méthodes d’optimisation semi-définie positive (SDP) dans le contexte de l’aide multicritère à la décision. Précisément, nous utilisons l’optimisation SDP afin d’apprendre les paramètres d’un modèle de fonction de valeur additive
Multiple-criteria decision analysis (MCDA) aims at providing support in order to make a decision. MCDA methods allow to handle choice, ranking and sorting problems. These methods usually involve the elicitation of models. Eliciting the parameters of these models is not trivial. Indirect elicitation methods simplify this task by learning the parameters of the decision model from preference statements issued by the decision maker (DM) such as “alternative a is preferred to alternative b” or “alternative a should be classified in the best category”. The information provided by the decision maker are usually parsimonious. The MCDA model is learned through an interactive process between the DM and the decision analyst. The analyst helps the DM to modify and revise his/her statements if needed. The process ends once a model satisfying the preferences of the DM is found. Preference learning (PL) is a subfield of machine learning which focuses on the elicitation of preferences. Algorithms in this subfield are able to deal with large data sets and are validated withartificial and real data sets. Data sets used in PL are usually collected from different sources and aresubject to noise. Unlike in MCDA, there is little or no interaction with the user in PL. The input data set is considered as a noisy sample of a “ground truth”. Algorithms used in this field have strong statistical properties that allow them to filter noise in the data sets.In this thesis, we develop learning algorithms to infer the parameters of MCDA models. Precisely, we develop a metaheuristic designed for learning the parameters of a MCDA sorting model called majority rule sorting (MR-Sort) model. This metaheuristic is assessed with artificial and real data sets issued from the PL field. We use the algorithm to deal with a real application in the medical domain. Then we modify the metaheuristic to learn the parameters of a more expressive model called the non-compensatory sorting (NCS) model. After that, we develop a new type of veto rule for MR-Sort and NCS models which allows to take criteria coalitions into account. The last part of the thesis introduces semidefinite programming (SDP) in the context of multiple-criteria decision analysis. We use SDP to learn the parameters of an additive value function model
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Raboun, Oussama. "Multiple Criteria Spatial Risk Rating." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLED066.

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La thèse est motivée par une étude de cas intéressante liée à l’évaluation du risque nucléaire. Le cas d’étude consiste à évaluer l’impact d’un accident nucléaire survenu dans le milieu marin. Ce problème comporte des caractéristiques spatiales, différents enjeux économiques et environnementaux, des connaissances incomplètes sur les potentiels acteurs et un nombre élevé de scénarios d’accident possibles. Le cas d’étude a été résolu en utilisant différentes techniques d’analyse décisionnelle telles que la comparaison des loteries et les outils MCDA (Multiple Criteria Decision Analysis).Une nouvelle méthode de classification ordinale, nommée Dynamic-R, est née de cette thèse, visant à fournir une notation complète et convaincante. La méthode développée a fourni des résultats intéressants au cas d’étude et des propriétés théoriques très intéressantes qui sont présenté dans les chapitres 6 et 7 de ce manuscrit
The thesis is motivated by an interesting case study related to environmental risk assessment. The case study problem consists on assessing the impact of a nuclear accident taking place in the marine environment. This problem is characterized by spatial characteristics, different assets characterizing the spatial area, incomplete knowledge about the possible stakeholders, and a high number of possible accident scenarios. A first solution of the case study problem was proposed where different decision analysis techniques were used such as lotteries comparison, and MCDA (Multiple Criteria Decision Analysis) tools. A new MCDA rating method, named Dynamic-R, was born from this thesis, aiming at providing a complete and convincing rating. The developed method provided interesting results to the case study, and very interesting theoretical properties that will be presented in chapters 6 and 7 of this manuscript
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Levy, Jason K. "Computer support for environmental multiple criteria decision analysis under uncertainty." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ60552.pdf.

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Belton, V. "A comparative study of methods for multiple criteria decision aiding." Thesis, University of Cambridge, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377201.

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Imam, Bisher. "Nonlinear uncertainty analysis for multiple criteria natural resource decision support systems." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/186949.

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The effects of uncertainties on the simulation component and the decision component of the USDA-ARS Water Quality Decision Support System (WQDSS) are studied. For the simulation component, a generalized second order covariance propagation equation for multiple response models is developed to account for model nonlinearities and complexities. The equation permits the calculation of the covariance matrix of several model responses as a function of their first and second order sensitivities to variations in model parameters and the cross moments of the parameter vector. The equation is complemented by developing an applied approach that aims to identify model nonlinearities, isolate response discontinuities, and simplify the computational efforts associated with analytical uncertainty analysis. As for the decision component, a generalized closed form solution of the WQDSS's decision model is derived to allow consideration of a vector of quantitative scale factors. The factors indicate the relative importance of the studied decision criteria. A procedure that is based on computing these scale factors and assigning importance orders proportional to the effects of the uncertainties on the scoring function transformation of the individual criteria is also developed and tested. To test the methodology, the covariance matrix of twelve model responses is estimated based on uncertainties in sixteen soil related parameters using (a) direct simulation, (b) first order propagation and (c) second order propagation. Comparing the first and second order propagated matrices to those resulting from actual simulations of four agricultural management systems attests to the superiority of the second order equation. The effects of uncertainties on the decision recommendations are identified through experimental combinations of three different importance orders and four possible alternative ranking schemes. Two of the importance orders and their associated scale factors are based on the uncertainties in evaluating decision criteria. The ranking methods are based on varying the point at which averaging of the data takes place with respect to the decision process. Results indicate that the decision model is less sensitive to changes in the point of averaging than it is with respect to variations in the importance orders and the scale factors.
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Cabrera, Rios Mauricio. "MULTIPLE CRITERIA OPTIMIZATION STUDIES IN REACTIVE IN-MOLD COATING." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1022105843.

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Løken, Espen. "Multi-Criteria Planning of Local Energy Systems with Multiple Energy Carriers." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1490.

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Background and Motivation

Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions.

It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria.

The thesis focuses on two important stages of a multi-criteria planning task:

- The initial structuring and modelling phase

- The decision-making phase

The Initial Structuring and Modelling Phase

It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project.

In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase.

The Decision-Making Phase

Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are.

Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method.

It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account.

The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives.

Summarizing

For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.

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Brestovac, Goran, and Robi Grgurina. "Applying Multi-Criteria Decision Analysis Methods in Embedded Systems Design." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-22013.

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In several types of embedded systems the applications are deployed both as software and as hardware components. For such systems, the partitioning decision is highly important since the implementation in software or hardware heavily influences the system properties. In the industry, it is rather common practice to take deployment decisions in an early stage of the design phase and based on a limited number of aspects. Often such decisions are taken based on hardware and software designers‟ expertise and do not account the requirements of the entire system and the project and business development constraints. This approach leads to several disadvantages such as redesign, interruption, etc. In this scenario, we see the need of approaching the partitioning process from a multiple decision perspective. As a consequence, we start by presenting an analysis of the most important and popular Multiple Criteria Decision Analysis (MCDA) methods and tools. We also identify the key requirements on the partitioning process. Subsequently, we evaluate all of the MCDA methods and tools with respect to the key partitioning requirements. By using the key partitioning requirements the methods and tools that the best suits the partitioning are selected. Finally, we propose two MCDA-based partitioning processes and validate their feasibility thorough an industrial case study.
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MILZ, GEOFFREY G. "Beyond Ad-Hoc: An Application of Multiple Criteria Decision Analysis in Emergency Planning and Response." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212072805.

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Books on the topic "Multiple criteria analysis"

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Greco, Salvatore, Matthias Ehrgott, and José Rui Figueira, eds. Multiple Criteria Decision Analysis. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3094-4.

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Belton, Valerie, and Theodor J. Stewart. Multiple Criteria Decision Analysis. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4.

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Carlos, Romero. Multiple criteria analysis for agricultural decisions. Amsterdam: Elsevier, 1989.

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Ehrgott, Matthias, José Rui Figueira, and Salvatore Greco, eds. Trends in Multiple Criteria Decision Analysis. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-5904-1.

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International Conference on MCDM (11th 1994 Coimbra, Portugal). Multicriteria analysis. New York: Springer-Verlag, 1997.

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Seo, Fumiko, and Masatoshi Sakawa. Multiple Criteria Decision Analysis in Regional Planning. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-4035-2.

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Matsatsinis, Nikolaos, and Evangelos Grigoroudis, eds. Preference Disaggregation in Multiple Criteria Decision Analysis. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90599-0.

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Larichev, Oleg I., and David L. Olson. Multiple Criteria Analysis in Strategic Siting Problems. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3245-0.

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Evans, Gerald W. Multiple Criteria Decision Analysis for Industrial Engineering. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, [2016] | Series: Operations research series; 12: CRC Press, 2016. http://dx.doi.org/10.1201/9781315381398.

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J, Stewart Theodor, ed. Multiple criteria decision analysis: An integrated approach. Boston: Kluwer Academic Publishers, 2002.

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Book chapters on the topic "Multiple criteria analysis"

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Moshkovich, Helen, Alexander Mechitov, and David Olson. "Verbal Decision Analysis." In Multiple Criteria Decision Analysis, 605–36. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3094-4_15.

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Belton, Valerie, and Theodor J. Stewart. "The Multiple Criteria Problem." In Multiple Criteria Decision Analysis, 13–33. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_2.

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Belton, Valerie. "An Integrating Data Envelopment Analysis With Multiple Criteria Decision Analysis." In Multiple Criteria Decision Making, 71–79. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2918-6_6.

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Belton, Valerie, and Theodor J. Stewart. "Introduction." In Multiple Criteria Decision Analysis, 1–12. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_1.

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Belton, Valerie, and Theodor J. Stewart. "MCDA in a Broader Context." In Multiple Criteria Decision Analysis, 293–329. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_10.

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Belton, Valerie, and Theodor J. Stewart. "An Integrated Approach to MCDA." In Multiple Criteria Decision Analysis, 331–43. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_11.

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Belton, Valerie, and Theodor J. Stewart. "Preference Modelling." In Multiple Criteria Decision Analysis, 79–118. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_4.

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Belton, Valerie, and Theodor J. Stewart. "Value Function Methods: Practical Basics." In Multiple Criteria Decision Analysis, 119–61. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_5.

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Belton, Valerie, and Theodor J. Stewart. "Value Function Methods: Indirect And Interactive." In Multiple Criteria Decision Analysis, 163–207. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_6.

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Belton, Valerie, and Theodor J. Stewart. "Goal and Reference Point Methods." In Multiple Criteria Decision Analysis, 209–32. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1495-4_7.

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Conference papers on the topic "Multiple criteria analysis"

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Jin, Ruichen, Wei Chen, and Timothy Simpson. "Comparative studies of metamodeling techniques under multiple modeling criteria." In 8th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4801.

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Kovaleva, Yulia, Mehdi Ostadhassan, and Naser Tamimi. "Optimizing microseismic design using multiple criteria decision analysis." In SEG Technical Program Expanded Abstracts 2017. Society of Exploration Geophysicists, 2017. http://dx.doi.org/10.1190/segam2017-17659945.1.

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Derek, Jurica, and Marjan Sikora. "Bicycle Route Planning Using Multiple Criteria GIS Analysis." In 2019 International Conference on Software, Telecommunications and Computer Networks (SoftCOM). IEEE, 2019. http://dx.doi.org/10.23919/softcom.2019.8903800.

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Ding, Bin, and Lianlu Sun. "An inventory classification model for multiple criteria ABC analysis." In 2011 8th International Conference on Service Systems and Service Management (ICSSSM 2011). IEEE, 2011. http://dx.doi.org/10.1109/icsssm.2011.5959351.

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Yan Li and Manoj A. Thomas. "A Multiple Criteria Decision Analysis (MCDA) Software Selection Framework." In 2014 47th Hawaii International Conference on System Sciences (HICSS). IEEE, 2014. http://dx.doi.org/10.1109/hicss.2014.141.

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Wang, Rui, GuangLi Nie, and Yong Shi. "Multiple Criteria Quadratic Programming for Fund Customer Churn Analysis." In 2011 Fourth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2011. http://dx.doi.org/10.1109/cso.2011.173.

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Sabri, Karim, Gérard E. Colson, Augustin M. Mbangala, and Daniel M. Dubois. "Multiple Criteria and Multiple Periods Performance Analysis: The Comparison of North African Railways." In COMPUTING ANTICIPATORY SYSTEMS: CASYS’07—Eighth International Conference. AIP, 2008. http://dx.doi.org/10.1063/1.3020675.

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Zhang, Peng, and Jingran Dai. "Multiple-Criteria Linear Programming for VIP E-Mail Behavior Analysis." In 2007 Seventh IEEE International Conference on Data Mining - Workshops (ICDM Workshops). IEEE, 2007. http://dx.doi.org/10.1109/icdmw.2007.45.

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Zhu, Meihong, Yong Shi, Aihua Li, and Peng Zhang. "A Bias-Variance Analysis of Multiple Criteria Linear Programming Classification Ensembles." In 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2008. http://dx.doi.org/10.1109/wiiat.2008.283.

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Mahammed, Nadir, Sidi Mohamed Benslimane, Ali Ouldkradda, and Mahmoud Fahsi. "Evolutionary Business Process Optimization using a Multiple-Criteria Decision Analysis method." In 2018 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 2018. http://dx.doi.org/10.1109/cits.2018.8440166.

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Reports on the topic "Multiple criteria analysis"

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Zhang, Linlin, Xiaoming Xi, Xihua Liu, Xinjie Qu, Qing Wang, Haihao Cao, Limin Wang, et al. Should aerobic and resistance training interventions for Multiple sclerosis be performed on the same day: A protocol for systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2021. http://dx.doi.org/10.37766/inplasy2021.12.0126.

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Review question / Objective: P (Population) : patients diagnosed with multiple sclerosis; I (Intervention) : aerobic training and resistance training; C (Comparison) : the efficacy and safety were compared on the same day and different days; O (Outcome) : Evaluates dysfunction, quality of life, fatigue, aerobic capacity or muscle function, mood, cognition, and safety. S (Study Design) : Systematic review and Network meta-analysis. Eligibility criteria: Measures in the intervention group: aerobic training (taijiquan, Baduanjin, qigong, yoga, swimming, cycling, jogging, brisk walking, etc.) and resistance training were used simultaneously, including studies conducted on the same day and on different days. There are no restrictions on training time, frequency and intensity.Control group measures: no intervention or conventional treatment.
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Horvit, Andrew, and Donald Molony. A Systematic Review and Meta-Analysis of Mortality and Kidney Function in Uranium – Exposed Individuals. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0122.

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Review question / Objective: 1) In humans, how does environmental and/or occupational exposure to uranium affect the risk of mortality due to primary kidney disease compared to unexposed individuals? (2) In humans, how does environmental and/or occupational exposure to uranium affect the risk of developing kidney failure compared to unexposed individuals? Eligibility criteria: We included cohort studies that evaluate the risk of CKD/ESKD due to uranium exposure. We also included cohort studies that evaluate standardized mortality due to all-cause mortality, kidney cancer, chronic kidney disease, diabetes, and cardiovascular disease in humans with exposure to uranium. We also included cross sectional studies that evaluate renal function in humans exposed to uranium via biomarkers and hard clinical measures (such as creatinine clearance) compared to humans with low/no uranium exposure. In order to not include the same cohort multiple times in the statistical analyses, we selected studies that evaluated an outcome of interest for a given cohort for the longest follow-up period. When this was not possible (due to multiple studies using different combinations of cohorts with varying lengths of follow up), the study with the largest study population size was selected.
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Sandeep, Bhushan, Huang Xin, and Xiao Zongwei. A comparison of regional anesthesia techniques in patients undergoing of video-assisted thoracic surgery: A network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2022. http://dx.doi.org/10.37766/inplasy2022.2.0003.

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Review question / Objective: Although video-assisted thoracoscopic surgery is a minimally invasive surgical technique, the pain remains moderate to severe. We comprehensively compared the regional anesthesia methods for postoperative analgesia in patients undergoing video-assisted thoracoscopic surgery. Eligibility criteria: All published full-article RCTs comparing the analgesic efficacy of investigated regional anesthesia technique or comparative blocks in adult patients undergoing any VATS were eligible for inclusion. There were no language restrictions. Moreover, we also excluded case reports, non-RCT studies, incomplete clinical trials, and any trials used multiple nerve blocks. We also excluded any conference abstracts which could not offer enough information about the study design, or by data request to the author.
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Bhushan, Sandeep, Huang Xin, and Xiao Zongwei. Ultrasound-guided erector spinae plane block for postoperative analgesia in patients undergoing liver surgery: what we might know from a meta-analysis of Randomized control trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, January 2022. http://dx.doi.org/10.37766/inplasy2022.1.0094.

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Condition being studied: ESPB as an emerging regional technique has been well established in many surgeries, including reduce opioid demands, decrease pain score and improver sleep quality, etc. But, apply ESPB in liver surgery is limiting and remains uncertain, it is time to conduct one meta-analysis to reveal the performance of ESPB in liver surgery. Eligibility criteria: All published full-article RCTs comparing the analgesic efficacy of ESPB with control in adult patients undergoing any liver surgeries were eligible for inclusion. There were no language restrictions, Moreover, we also excluded case reports, non-RCT studies, incomplete clinical trials, and any trials used multiple nerve blocks. We also excluded any conference abstracts which could not offer enough information about the study design, or by data request to the author.
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Kürşat Önder, Yasin, Maria Alejandra Ruiz-Sanchez, Sara Restrepo-Tamayo, and Mauricio Villamizar-Villegas. Government Borrowing and Crowding Out. Banco de la República, December 2021. http://dx.doi.org/10.32468/be.1182.

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We investigate the impact of fiscal expansions on firm investment by exploiting firms that have multiple banking relationships. Further, we conduct a localized RDD approach and compare the lending behavior of banks that barely met and missed the criteria of being a primary dealer, as well as barely winners and losers at government auctions. Our results indicate that a 1 percentage point increase in banks’ bonds-to-assets ratio decreases loans by up to 0.4%, which leads to significant declines in firm investment, profits and wages. Our findings are grounded in a quantitative model with financial and real sectors with which we undertake a welfare analysis and compute the cost of government borrowing on the overall economy.
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Selph, Shelly S., Andrea C. Skelly, Ngoc Wasson, Joseph R. Dettori, Erika D. Brodt, Erik Ensrud, Diane Elliot, et al. Physical Activity and the Health of Wheelchair Users: A Systematic Review in Multiple Sclerosis, Cerebral Palsy, and Spinal Cord Injury. Agency for Healthcare Research and Quality (AHRQ), October 2021. http://dx.doi.org/10.23970/ahrqepccer241.

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Objectives. Although the health benefits of physical activity are well described for the general population, less is known about the benefits and harms of physical activity in people dependent upon, partially dependent upon, or at risk for needing a wheelchair. This systematic review summarizes the evidence for physical activity in people with multiple sclerosis, cerebral palsy, and spinal cord injury regardless of current use or nonuse of a wheelchair. Data sources. We searched MEDLINE®, CINAHL®, PsycINFO®, Cochrane CENTRAL, Embase®, and Rehabilitation and Sports Medicine Source from 2008 through November 2020, reference lists, and clinical trial registries. Review methods. Predefined criteria were used to select randomized controlled trials, quasiexperimental nonrandomized trials, and cohort studies that addressed the benefits and harms of observed physical activity (at least 10 sessions on 10 different days of movement using more energy than rest) in participants with multiple sclerosis, cerebral palsy, and spinal cord injury. Individual study quality (risk of bias) and the strength of bodies of evidence for key outcomes were assessed using prespecified methods. Dual review procedures were used. Effects were analyzed by etiology of impairment and physical activity modality, such as treadmill, aquatic exercises, and yoga, using qualitative, and when appropriate, quantitative synthesis using random effects meta-analyses. Results. We included 146 randomized controlled trials, 15 quasiexperimental nonrandomized trials, and 7 cohort studies (168 studies in 197 publications). More studies enrolled participants with multiple sclerosis (44%) than other conditions, followed by cerebral palsy (38%) and spinal cord injury (18%). Most studies were rated fair quality (moderate risk of bias). The majority of the evidence was rated low strength. • In participants with multiple sclerosis, walking ability may be improved with treadmill training and multimodal exercise regimens that include strength training; function may be improved with treadmill training, balance exercises, and motion gaming; balance is likely improved with postural control exercises (which may also reduce risk of falls) and may be improved with aquatic exercises, robot-assisted gait training, treadmill training, motion gaming, and multimodal exercises; activities of daily living may be improved with aquatic therapy; sleep may be improved with aerobic exercises; aerobic fitness may be improved with multimodal exercises; and female sexual function may be improved with aquatic exercise. • In participants with cerebral palsy, balance may be improved with hippotherapy and motion gaming, and function may be improved with cycling, treadmill training, and hippotherapy. • In participants with spinal cord injury, evidence suggested that activities of daily living may be improved with robot-assisted gait training. • When randomized controlled trials were pooled across types of exercise, physical activity interventions were found to improve walking in multiple sclerosis and likely improve balance and depression in multiple sclerosis. Physical activity may improve function and aerobic fitness in people with cerebral palsy or spinal cord injury. When studies of populations with multiple sclerosis and cerebral palsy were combined, evidence indicated dance may improve function. • Evidence on long-term health outcomes was not found for any analysis groups. For intermediate outcomes such as blood pressure, lipid profile, and blood glucose, there was insufficient evidence from which to draw conclusions. There was inadequate reporting of adverse events in many trials. Conclusions. Physical activity was associated with improvements in walking ability, general function, balance (including fall risk), depression, sleep, activities of daily living, female sexual function, and aerobic capacity, depending on population enrolled and type of exercise utilized. No studies reported long-term cardiovascular or metabolic disease health outcomes. Future trials could alter these findings; further research is needed to examine health outcomes, and to understand the magnitude and clinical importance of benefits seen in intermediate outcomes.
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Tosi, R., R. Codina, J. Principe, R. Rossi, and C. Soriano. D3.3 Report of ensemble based parallelism for turbulent flows and release of solvers. Scipedia, 2022. http://dx.doi.org/10.23967/exaqute.2022.3.06.

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In this work we focus on reducing the wall clock time required to compute statistical estimators of highly chaotic incompressible flows on high performance computing systems. Our approach consists of replacing a single long-term simulation by an ensemble of multiple independent realizations, which are run in parallel with different initial conditions. A failure probability convergence criteria must be satisfied by the statistical estimator of interest to assess convergence. Its error analysis leads to the identification of two error contributions: the initialization bias and the statistical error. We propose an approach to systematically detect the burn-in time in order to minimize the initialization bias, accompanied by strategies to reduce simulation cost. The framework is validated on two very high Reynolds number obstacle problems of wind engineering interest in a high performance computing environment.
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Ekegren, Michael, and Sandra LeGrand. Incorporating terrain roughness into helicopter landing zone site selection by using the Geomorphic Oscillation Assessment Tool (GOAT) v1.0. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42162.

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The Geomorphic Oscillation Assessment Tool (GOAT) quantifies terrain roughness as a mechanism to better explain forward arming and refueling point (FARP) suitability for Army aviation. An empirically driven characteristic of FARP consideration, surface roughness is a key discriminator for site utility in complex terrain. GOAT uses a spatial sampling of high-resolution elevation and land cover data to construct data frames, which enable a relational analysis of component and aggregate site suitability. By incorporating multiple criteria from various doctrinal sources, GOAT pro-duces a composite quality assessment of the areal options available to the aviation commander. This report documents and demonstrates version 1.0 of the GOAT algorithms developed by the U.S. Army Engineer Research and Development Center (ERDC). These details will allow users familiar with R to implement it as a stand-alone program or in R Studio.
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Sitabkhan, Yasmin, and Linda M. Platas. Early Mathematics Counts: Promising Instructional Strategies from Low- and Middle-Income Countries. RTI Press, July 2018. http://dx.doi.org/10.3768/rtipress.2018.op.0055.1807.

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This occasional paper examines common instructional strategies in early-grade mathematics interventions through a review of studies in classrooms in low- and middle-income countries. Twenty-four studies met the criteria for inclusion, and analyses reveal four sets of instructional strategies for which there is evidence from multiple contexts. Of the 24 studies, 16 involved the use of multiple representations, 10 involved the use of developmental progressions, 6 included supporting student use of explanation and justification, and 5 included integration of informal mathematics. Based on the review, we provide conclusions and recommendations for future research and policy.
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Michalak, Julia, Josh Lawler, John Gross, and Caitlin Littlefield. A strategic analysis of climate vulnerability of national park resources and values. National Park Service, September 2021. http://dx.doi.org/10.36967/nrr-2287214.

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The U.S. national parks have experienced significant climate-change impacts and rapid, on-going changes are expected to continue. Despite the significant climate-change vulnerabilities facing parks, relatively few parks have conducted comprehensive climate-change vulnerability assessments, defined as assessments that synthesize vulnerability information from a wide range of sources, identify key climate-change impacts, and prioritize vulnerable park resources (Michalak et al. In review). In recognition that funding and planning capacity is limited, this project was initiated to identify geographies, parks, and issues that are high priorities for conducting climate-change vulnerability assessments (CCVA) and strategies to efficiently address the need for CCVAs across all U.S. National Park Service (NPS) park units (hereafter “parks”) and all resources. To help identify priority geographies and issues, we quantitatively assessed the relative magnitude of vulnerability factors potentially affecting park resources and values. We identified multiple vulnerability factors (e.g., temperature change, wildfire potential, number of at-risk species, etc.) and sought existing datasets that could be developed into indicators of these factors. To be included in the study, datasets had to be spatially explicit or already summarized for individual parks and provide consistent data for at least all parks within the contiguous U.S. (CONUS). The need for consistent data across such a large geographic extent limited the number of datasets that could be included, excluded some important drivers of climate-change vulnerability, and prevented adequate evaluation of some geographies. The lack of adequately-scaled data for many key vulnerability factors, such as freshwater flooding risks and increased storm activity, highlights the need for both data development and more detailed vulnerability assessments at local to regional scales where data for these factors may be available. In addition, most of the available data at this scale were related to climate-change exposures, with relatively little data available for factors associated with climate-change sensitivity or adaptive capacity. In particular, we lacked consistent data on the distribution or abundance of cultural resources or accessible data on infrastructure across all parks. We identified resource types, geographies, and critical vulnerability factors that lacked data for NPS’ consideration in addressing data gaps. Forty-seven indicators met our criteria, and these were combined into 21 climate-change vulnerability factors. Twenty-seven indicators representing 12 vulnerability factors addressed climate-change exposure (i.e., projected changes in climate conditions and impacts). A smaller number of indictors measured sensitivity (12 indicators representing 5 vulnerability factors). The sensitivity indicators often measured park or landscape characteristics which may make resources more or less responsive to climate changes (e.g., current air quality) as opposed to directly representing the sensitivity of specific resources within the park (e.g., a particular rare species or type of historical structure). Finally, 6 indicators representing 4 vulnerability factors measured external adaptive capacity for living resources (i.e., characteristics of the park and/or surrounding landscape which may facilitate or impede species adaptation to climate changes). We identified indicators relevant to three resource groups: terrestrial living, aquatic living (including living cultural resources such as culturally significant landscapes, plant, or animal species) and non-living resources (including infrastructure and non-living cultural resources such as historic buildings or archeological sites). We created separate indicator lists for each of these resource groups and analyzed them separately. To identify priority geographies within CONUS,...
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