Relevant bibliographies by topics / Optimization-simulation modelling

Academic literature on the topic 'Optimization-simulation modelling'

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Published: 6 September 2023

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Journal articles on the topic "Optimization-simulation modelling"

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Wang, Cheng-Chi. "Applied Modelling, Numerical Simulation and Optimization." Applied Mathematical Modelling 47 (July 2017): 755. http://dx.doi.org/10.1016/j.apm.2017.05.025.

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Stanković, Ratko, and Diana Božić. "Applying Simulation Modelling in Quantifying Optimization Results." Tehnički glasnik 15, no. 4 (November 1, 2021): 518–23. http://dx.doi.org/10.31803/tg-20210326111551.

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Improvements achieved by applying linear programming models in solving optimization problems in logistics cannot always be expressed by physically measurable values (dimensions), but in non-dimensional values. Therefore, it may be difficult to present the actual benefits of the improvements to the stake holders of the system being optimized. In this article, a possibility of applying simulation modelling in quantifying results of optimizing cross dock terminal gates allocation is outlined. Optimal solution is obtained on the linear programming model by using MS Excel spreadsheet optimizer, while the results are quantified on the simulation model, by using Rockwell Automation simulation software. Input data are collected from a freight forwarding company in Zagreb, specialized in groupage transport (Less Than Truckload - LTL).
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Yang, Xin-She, and Slawomir Koziel. "Computational optimization, modelling and simulation–a paradigm shift." Procedia Computer Science 1, no. 1 (May 2010): 1297–300. http://dx.doi.org/10.1016/j.procs.2010.04.144.

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Husain, Asghar, Ali Hassan, Darwish M. K. Al-Gobaisi, Adil Al-Radif, A. Woldai, and C. Sommariva. "Modelling, simulation, optimization and control of multistage flashing (MSF) desalination plants Part I: Modelling and simulation." Desalination 92, no. 1-3 (July 1993): 21–41. http://dx.doi.org/10.1016/0011-9164(93)80073-v.

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Kodym, Oldřich, Zdeněk Čujan, Michal Turek, and Nikoleta Mikušová. "Optimization of material flow using simulation." MATEC Web of Conferences 263 (2019): 01007. http://dx.doi.org/10.1051/matecconf/201926301007.

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The strategic aim of all production enterprises is to achieve the highest possible profit, for which they use attributes of lean production that are related and support the reduction of production costs. Using of theoretical knowledge and realization of a detailed analysis of a material flow including mapping of individual production processes it is possible to obtain the necessary data sets identifying savings options by increasing of efficiency, including cost savings. Methods of modelling and simulation were used for the optimization of material flow.
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Westermann, Paul, Theodor Christiaanse, Will Beckett, Paul Kovacs, and Ralph Evins. "besos: Building and Energy Simulation, Optimization and Surrogate Modelling." Journal of Open Source Software 6, no. 60 (April 6, 2021): 2677. http://dx.doi.org/10.21105/joss.02677.

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Yang, Xin-She, Slawomir Koziel, and Leifur Leifsson. "Computational Optimization, Modelling and Simulation: Recent Trends and Challenges." Procedia Computer Science 18 (2013): 855–60. http://dx.doi.org/10.1016/j.procs.2013.05.250.

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Yang, Xin-She, Slawomir Koziel, and Leifur Leifsson. "Computational Optimization, Modelling and Simulation: Past, Present and Future." Procedia Computer Science 29 (2014): 754–58. http://dx.doi.org/10.1016/j.procs.2014.05.067.

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Yang, Xin-She, Slawomir Koziel, and Leifur Leifsson. "Computational optimization, modelling and simulation: Recent advances and overview." Procedia Computer Science 4 (2011): 1230–33. http://dx.doi.org/10.1016/j.procs.2011.04.132.

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Lu, C. J. J., K. H. Tsai, J. C. S. Yang, and Y. M. Wang. "Real-Time Operation Plan Optimization Using Accelerated Simulation Modelling." International Journal of Modelling and Simulation 16, no. 4 (January 1996): 184–91. http://dx.doi.org/10.1080/02286203.1996.11760298.

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Dissertations / Theses on the topic "Optimization-simulation modelling"

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Ibrahim, Rashidi. "Vibration assisted machining : modelling, simulation, optimization, control and applications." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/4732.

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Increasing demand for precision components made of hard and brittle materials such as glasses, steel alloys and advanced ceramics, is such that conventional grinding and polishing techniques can no longer meet the requirements of today's precision manufacturing engineering. Particularly, in order to undertake micro-milling of optical glasses or other hard-machining materials, vibration assisted machining techniques have been adopted. However, it is essential and much needed to undertake such processes based on a scientific approach, i.e. the process to be quantitatively controlled and optimized rather than carried out with a trial-and-error manner. In this research, theoretical modelling and instrumental implementation issues for vibration assisted micro-milling are presented and explored in depth. The modelling is focused on establishing the scientific relationship between the process variables such as vibration frequency, vibration amplitude, feedrate and spindle speed while taking into account machine dynamics effect and the outcomes such as surface roughness generated, tool wear and material removal rate in the process. The machine dynamics has been investigated including a static analysis, machine tool-loop stiffness, modal analysis, frequency response function, etc, carried out for both the machine structure and the piezo-actuator device. The instrumentation implementation mainly includes the design of the desktop vibration assisted machining system and its control system. The machining system consists of a piezo-driven XY stage, air bearing spindle, jig, workpiece holder, PI slideway, manual slideway and solid metal table to improve the system stability. The control system is developed using LabVIEW 7.1 programming. The control algorithms are developed based on theoretical models developed by the author. The process optimisation of vibration assisted micro-milling has been studied by using design and analysis of experiment (DOE) approach. Regression analysis, analysis of variance (ANOVA), Taguchi method and Response Surface Methodology (RSM) have been chosen to perform this study. The effects of cutting parameters are evaluated and the optimal cutting conditions are determined. The interaction of cutting parameters is established to illustrate the intrinsic relationship between cutting parameters and surface roughness, tool wear and material removal rate. The predicted results are confirmed by validation experimental cutting trials. This research project has led to the following contribution to knowledge: (1) Development of a prototype desktop vibration assisted micro-milling machine. (2) Development of theoretical models that can predict the surface finish, tool wear and material removal rate quantitatively. (3) Establishing in depth knowledge on the use of vibration assisted machining principles. (4) Optimisation of cutting process parameters and conditions through simulations and machining trials for through investigation of vibration assisted machining.
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Sun, Yan. "Modelling, simulation and optimization of near-ambient grain drying." Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243324.

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Siurana, Paula Maria. "Modelling and multiobjective optimization for simulation of cyanobacterial metabolism." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/90578.

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The present thesis is devoted to the development of models and algorithms to improve metabolic simulations of cyanobacterial metabolism. Cyanobacteria are photosynthetic bacteria of great biotechnological interest to the development of sustainable bio-based manufacturing processes. For this purpose, it is fundamental to understand metabolic behaviour of these organisms, and constraint-based metabolic modelling techniques offer a platform for analysis and assessment of cell's metabolic functionality. Reliable simulations are needed to enhance the applicability of the results, and this is the main goal of this thesis. This dissertation has been structured in three parts. The first part is devoted to introduce needed fundamentals of the disciplines that are combined in this work: metabolic modelling, cyanobacterial metabolism and multi-objective optimisation. In the second part the reconstruction and update of metabolic models of two cyanobacterial strains is addressed. These models are then used to perform metabolic simulations with the application of the classic Flux Balance Analysis (FBA) methodology. The studies conducted in this part are useful to illustrate the uses and applications of metabolic simulations for the analysis of living organisms. And at the same time they serve to identify important limitations of classic simulation techniques based on mono-objective linear optimisation that motivate the search of new strategies. Finally, in the third part a novel approach is defined based on the application of multi-objective optimisation procedures to metabolic modelling. Main steps in the definition of multi-objective problem and the description of an optimisation algorithm that ensure the applicability of the obtained results, as well as the multi-criteria analysis of the solutions are covered. The resulting tool allows the definition of non-linear objective functions and constraints, as well as the analysis of multiple Pareto-optimal solutions. It avoids some of the main drawbacks of classic methodologies, leading to more flexible simulations and more realistic results. Overall this thesis contributes to the advance in the study of cyanobacterial metabolism by means of definition of models and strategies that improve plasticity and predictive capacities of metabolic simulations.
La presente tesis está dedicada al desarrollo de modelos y algoritmos para mejorar las simulaciones metabólicas de cianobacterias. Las cianobacterias son bacterias fotosintéticas de gran interés biotecnológico para el desarrollo de bioprocesos productivos sostenibles. Para este propósito, es fundamental entender el comportamiento metabólico de estos organismos, y el modelado metabólico basado en restricciones ofrece una plataforma para el análisis y la evaluación de las funcionalidades metabólicas de las células. Se necesitan simulaciones fidedignas para aumentar la aplicabilidad de los resultados, y este es el objetivo principal de esta tesis. Esta disertación se ha estructurado en tres partes. La primera parte está dedicada a introducir los fundamentos necesarios de las disciplinas que se combinan en este trabajo: el modelado metabólico, el metabolismo de cianobacterias, y la optimización multiobjetivo. En la segunda parte, se encara la reconstrucción y la actualización de los modelos metabólicos de dos cepas de cianobacterias. Estos modelos se usan después para llevar a cabo simulaciones metabólicas con la aplicación de la metodología clásica Flux Balance Analysis (FBA). Los estudios realizados en esta parte son útiles para ilustrar los usos y aplicaciones de las simulaciones metabólicas para el análisis de los organismos vivos. Y al mismo tiempo sirven para identificar importantes limitaciones de las técnicas clásicas de simulación basadas en optimización lineal mono-objetivo que motivan la búsqueda de nuevas estrategias. Finalmente, en la tercera parte, se define una nueva aproximación basada en la aplicación al modelado metabólico de procedimientos de optimización multiobjetivo. Se cubren los principales pasos en la definición de un problema multiobjetivo y la descripción de un algoritmo de optimización que aseguren la aplicabilidad de los resultados obtenidos, así como el análisis multi-criterio de las soluciones. La herramienta resultante permite la definición de funciones objetivo y restricciones no lineales, así como el análisis de múltiples soluciones en el sentido de Pareto. Esta herramienta evita algunos de los principales inconvenientes de las metodologías clásicas, lo que lleva a obtener simulaciones más flexibles y resultados más realistas. En conjunto, esta tesis contribuye al avance en el estudio del metabolismo de cianobacterias por medio de la definición de modelos y estrategias que mejoran la plasticidad y las capacidades predictivas de las simulaciones metabólicas.
La present tesi està dedicada al desenvolupament de models i algorismes per a millorar les simulacions metabòliques de cianobacteris. Els cianobacteris són bacteris fotosintètics de gran interés biotecnològic per al desenvolupament de bioprocessos productius sostenibles. Per a aquest propòsit, és fonamental entendre el comportament metabòlic d'aquests organismes, i el modelatge metabòlic basat en restriccions ofereix una plataforma per a l'anàlisi i l'avaluació de les funcionalitats metabòliques de les cèl·lules. Es necessiten simulacions fidedignes per a augmentar l'aplicabilitat dels resultats, i aquest és l'objectiu principal d'aquesta tesi. Aquesta dissertació s'ha estructurat en tres parts. La primera part està dedicada a introduir els fonaments necessaris de les disciplines que es combinen en aquest treball: el modelatge metabòlic, el metabolisme de cianobacteris i l'optimització multiobjectiu. En la segona part, s'adreça la reconstrucció i l'actualització dels models metabòlics de dos soques de cianobacteris. Aquests models s'empren després per a portar a terme simulacions metabòliques amb l'aplicació de la metodologia clàssica Flux Balance Analysis (FBA). Els estudis realitzats en aquesta part són útils per a il·lustrar els usos i aplicacions de les simulacions metabòliques per a l'anàlisi dels organismes vius. I al mateix temps serveixen per a identificar importants limitacions de les tècniques clàssiques de simulació basades en optimització lineal mono-objectiu que motiven la cerca de noves estratègies. Finalment, en la tercera part, es defineix una nova aproximació basada en l'aplicació al modelatge metabòlic de procediments d'optimització multiobjectiu. Es cobreixen els principals passos en la definició d'un problema multiobjectiu i la descripció d'un algorisme d'optimització que asseguren l'aplicabilitat dels resultats obtinguts, així com l'anàlisi multi-criteri de les solucions. La ferramenta resultant permet la definició de funcions objectiu i restriccions no lineals, així com l'anàlisi de múltiples solucions òptimes en el sentit de Pareto. Aquesta ferramenta evita alguns dels principals inconvenients de les metodologies clàssiques, el que porta a obtenir simulacions més flexibles i resultats més realistes. En conjunt, aquesta tesi contribueix a l'avanç en l'estudi del metabolisme de cianobacteris per mitjà de la definició de models i estratègies que milloren la plasticitat i les capacitats predictives de les simulacions metabòliques.
Siurana Paula, M. (2017). Modelling and multiobjective optimization for simulation of cyanobacterial metabolism [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90578
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Ashaibani, A. S. "Modelling simulation and optimization of refinery processess with energy conservation." Thesis, University of Bradford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511389.

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Aris, Najmil Faiz Mohamed. "Surfaces functionality of precision machined components : modelling, simulation, optimization and control." Thesis, Brunel University, 2008. http://bura.brunel.ac.uk/handle/2438/5092.

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This research develops an analytical scientific approach for investigating the high precision surface generation and the quantitative analysis of the effects of direct factors in precision machining. The research focuses on 3D surface characterization with particular reference to the turning process and associated surface generation. The most important issue for this research is surface functionality which is becoming important in the current engineering industry. The surface functionality should match with the characterization parameters of the machined surface, which can be expressed in formula form as proposed in chapter 4. Modelling and simulation are extensively used in the research. The modelling approach integrates the cutting forces model, thermal mode% vibration model, tool wear model, machining system response model and surface topography model. All of those models are integrated as a whole model. The physical model with such as direct inputs is formed. The major inputs to the model are tooling geometry and the process variables. The outputs from the modelling approach are cutting force, surface texture parameters, dimensional errors, residual stress and material removal rate. MATLAB and Simulink are used as tools to implement the modelling and simulation. According to the simulation results, it is found that the feed rate has the most profound effect on in surface generation. The influence of the vibrations between the cutting tool and the workpiece on the surface roughness may be minimised by the small feed rate and large tool nose radius. Surface functionality simulation has been developed to model and simulate the surface generation in precision turning. The surface functionality simulation model covers the material and tool wear as well. It shows that chip formation is resulted from cutting forces. Cutting trials are conducted to validate the modelling and simulation developed. There are positive results that show the agreement between the simulation and experimental results. The analysis of the results of turning trials and simulations are conducted in order to find out the effects of process variables and tooling characteristics on surface texture and topography and machining instability. From the research, it can be concluded that the investigation on modelling and simulation of precision surfaces generation in precision turning is performed well against the research objectives as proposed. Recommendations for future work are to improve the model parameters identification, including comprehensive tool wear, chip formation and using Neural Networks modelling in the engineering surface construction system.
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Scaglioso, Giovanni. "Modelling, simulation and optimization of maintenance considerations on condition based maintenance." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8308/.

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Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.
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Achermann, David. "Modelling, simulation and optimization of maintenance strategies under consideration of logistic processes /." Zürich : ETH, 2008. http://opac.nebis.ch/cgi-bin/showAbstract.pl?sys=000259627.

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Pang, Xi. "Trade-off analysis of forest ecosystem services – A modelling approach." Doctoral thesis, KTH, Hållbarhet, utvärdering och styrning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216432.

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Forest is a resource that is increasingly utilized for multiple purposes. The balance between energy demands and the long-term capacity of ecosystems to support biodiversity and other ecosystem services is crucial. The aim of this project was to increase the knowledge on and to develop methods and tools for trade-offs and synergies analysis among forest ecosystem services based on different forest management policies. Paper I provides an overview of existing models for integrated energy-environment assessment. A literature review was conducted on assessment models and their ability to integrate energy with environmental aspects. Missing environmental aspects concern land use, landscapes and biodiversity. In Paper II a modelling framework was set up to link a landscape simulator with a habitat network model for integrated assessment of bioenergy feedstock and biodiversity related impacts in Kronoberg County. In Paper III we continued with the same management scenarios, while the analysis was expanded to five ecosystem services by developing the Landscape simulation and Ecological Assessment (LEcA) tool: industrial wood, bioenergy, forest carbon stock, recreation areas and habitat networks. In Paper IV we present two heuristic methods for spatial optimization – simulated annealing (SA) and genetic algorithm (GA) – to find optimal solutions for allocating harvest activities, in order to minimize the impacts on habitat networks. In Paper V, as response to the findings in Paper I, we linked the energy model MESSAGE with our LEcA tool for forest bioenergy demand assessment while applying environmental and transport restrictions, in a study of Lithuania. We found trade-offs between industrial wood production and bioenergy on one side, and recreation values, biodiversity, and to some extent carbon storage on the other side. The LEcA tool integrated forest simulation and management with assessment of ecosystem services, which is promising for integrated sustainability assessment of forest management policies.

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Dritsas, Ioannis. "Stochastic modelling and simulation-based optimization of specialty fibres for high power fibre lasers." Thesis, City University London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446447.

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Vasini, Ester Maria <1986&gt. "Numerical Modelling and Simulation Optimization of Geothermal Reservoirs Using the Tough2 Family of Codes." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amsdottorato.unibo.it/7412/1/Vasini_EsterMaria_tesi.pdf.

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In order to improve the reservoir engineering activities and, in particular, to optimize numerical modelling and simulation of geothermal reservoirs using the TOUGH family of codes, it has been decided to use the software T2Well for the interpretation of well-tests, coupling T2Well with the equation of state module EWASG, which describes the typical thermodynamic condition in high enthalpy geothermal reservoirs. T2Well-EWASG has been coupled and tested through the typical process of verification and validation. The application of T2Well-EWASG for the interpretation of well-tests related to the slim hole WW-01 drilled in the Wotten Waven Field (Commonwealth of Dominica) proves that it can be used as a tool for integrated interpretation of surface and downhole measurements collected during the performance of production tests in geothermal wells. The strength of this tool is that it allows to reduce the different possible solutions (in terms of reservoir characterization) within an acceptable error, by allowing the interpretation of surface and downhole measurements in conjunction, instead of separately. From this point of view T2Well-EWASG can effectively be used as a tool which allows an improvement of reservoir engineering activities. Finally, the huge amount of data managed during these activities has permitted to test and project the improvement of pre- and post- processing tools specific for TOUGH2 created by the geothermal research group of DICAM. In particular, the pre- and post-processing tools have been validated with a case study dealing with the migration of non-condensable gases in deep sedimentary formation.
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Books on the topic "Optimization-simulation modelling"

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Hasle, Geir, Knut-Andreas Lie, and Ewald Quak, eds. Geometric Modelling, Numerical Simulation, and Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-68783-2.

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E, Edwards John. Process simulation refinery processes: Modelling and optimization. Thornaby: P & I Design Ltd, 2013.

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1946-, Elshishini S. S., ed. Modelling, simulation, and optimization of industrial fixed bed catalytic reactors. Yverdon, Switzerland: Gordon and Breach Science Publishers, 1993.

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1953-, Hasle Geir, Lie Knut A, Quak Ewald, and Selskapet for industriell og teknisk forskning ved Norges tekniske høgskole., eds. Geometric modelling, numerical simulation, and optimization: Applied mathematics at SINTEF. Berlin: Springer, 2007.

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International, Workshop on Modelling Simulation and Optimization (2008 Hong Kong China). 2008 International Workshop on Modelling, Simulation and Optimization: Proceedings, Hong Kong, 27-28 December 2008. Los Alamitos, Calif: IEEE Computer Society, 2009.

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Andreas, Kroll, ed. Hydraulic Servo-systems: Modelling, Identification and Control. London: Springer London, 2003.

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Allaire, Grégoire. Numerical analysis and optimization: An introduction to mathematical modelling and numerical simulation. Oxford: Oxford University Press, 2007.

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Allaire, Grégoire. Numerical analysis and optimization: An introduction to mathematical modelling and numerical simulation. Oxford: Oxford University, 2007.

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IASTED International Symposium: Modelling, Simulation and Optimization (1990 Montréal, Quebec). Proceedings of the IASTED International Symposium, Modelling, Simulation and Optimization: Montreal, Canada, May 22-24, 1990. Edited by Jacyno Z and International Association of Science and Technology for Development. Anaheim, Calif: Acta Press, 1990.

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Singapore), IASTED International Conference: Modelling Simulation and Optimization (1997. Proceedings of the IASTED International Conference, Modelling, Simulation and Optimization (MSO '97), August 11-13, 1997, Singapore. Anaheim, Calif: IASTED/Acta Press, 1997.

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Book chapters on the topic "Optimization-simulation modelling"

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Birta, Louis G., and Gilbert Arbez. "Simulation Optimization in the CTDS Domain." In Modelling and Simulation, 359–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18869-6_11.

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Birta, Louis G., and Gilbert Arbez. "Simulation Optimization in the DEDS Domain." In Modelling and Simulation, 369–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18869-6_12.

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Singh, Randheer, Vikas Kukshal, and Vinod Singh Yadav. "Mathematical Modelling, Design and Simulation of a Bipedal Walker." In Modeling, Simulation and Optimization, 531–44. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_42.

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Hashunao, Somila, Hano Sunku, and R. K. Mehta. "Modelling and Forecasting of Solar Radiation Data: A Case Study." In Modeling, Simulation and Optimization, 1–13. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_1.

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Tsoi, Ye B., and S. V. Tishkovskaya. "Simulation and optimization of complex systems reliability characteristics in grouped data structure." In System Modelling and Optimization, 355–62. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-0-387-34897-1_42.

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Sakalauskas, Leonidas. "Simulation-Based Modelling of a Stochastic Equilibrium." In Uncertainty Management in Simulation-Optimization of Complex Systems, 55–75. Boston, MA: Springer US, 2015. http://dx.doi.org/10.1007/978-1-4899-7547-8_3.

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Hao, Zhengzheng. "Simulation and Optimization of AES." In An Integrated Modelling Approach to Design Cost-Effective AES for Agricultural Soil Erosion and Water Pollution, 135–46. Wiesbaden: Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-41340-8_8.

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Hanne, Thomas, and Rolf Dornberger. "Computational Intelligence in Modelling, Simulation, Optimization, and Control." In Business Information Systems and Technology 4.0, 227–41. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74322-6_15.

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Goodyer, Christopher, Jason Wood, and Martin Berzins. "Mathematical Modelling of Chemical Diffusion through Skin using Grid-based PSEs." In Modeling, Simulation and Optimization of Complex Processes, 249–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79409-7_16.

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Antony, Joseph, Mike J. Frisch, and Alistair P. Rendell. "Modelling the Performance of the Gaussian Chemistry Code on x86 Architectures." In Modeling, Simulation and Optimization of Complex Processes, 49–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79409-7_4.

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Conference papers on the topic "Optimization-simulation modelling"

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Fagerstrom, Sven E., and Nagy N. Bengiamin. "Buck/Boost Converter Modeling and Simulation for Performance Optimization." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.735-079.

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Lan, Guo-xing, and Feng Ye. "Research on System of Systems Simulation Optimization." In Applied Simulation and Modelling. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.715-070.

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Otamendi, J. "Simulation-Optimization In Geographic Maintenance Scheduling." In 21st Conference on Modelling and Simulation. ECMS, 2007. http://dx.doi.org/10.7148/2007-0062.

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Baeck, Thomas. "Algorithms for Simulation-Based Optimization Problems." In 32nd Conference on Modelling and Simulation. ECMS, 2018. http://dx.doi.org/10.7148/2018-0005.

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Chen, Li-ming. "Evaluation Modelling and Optimization of Investment Options." In 2008 International Workshop on Modelling, Simulation and Optimization. IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.18.

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Felice, Fabio De, and Antonella Petrillo. "Simulation Approach for the Optimization of the Layout in a Manufacturing Firm." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.802-047.

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Gavanelli, Marco, Michela Milano, Alan Holland, and Barry O'Sullivan. "What-If Analysis Through Simulation-Optimization Hybrids." In 26th Conference on Modelling and Simulation. ECMS, 2012. http://dx.doi.org/10.7148/2012-0624-0630.

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Zhu, Yunming, and Guicheng Wang. "Simulation Model and Mechanism of Burr Formation." In 2008 International Workshop on Modelling, Simulation and Optimization. IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.60.

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Kenzap, Serguei A., and Vassilios N. Kazakidis. "Optimization of Operating Risk in Mining System through Monte-Carlo Simulation." In Applied Simulation and Modelling. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.715-004.

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Dai, Ning, Lei Zhang, and Jianyu Wang. "Analysis and Simulation of the GPS-Pseudolite Signals." In 2008 International Workshop on Modelling, Simulation and Optimization. IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.22.

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Reports on the topic "Optimization-simulation modelling"

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Sanz, Asier`. Numerical simulation tools for PVT collectors and systems. IEA SHC Task 60, September 2020. http://dx.doi.org/10.18777/ieashc-task60-2020-0006.

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The computer-based experimentation covers almost the entire activity chain of the PVT sector. The PVT community carries out very different kind of modelling and simulation labours in order to answer to very diverse needs, such as proof-of-concepts, research, design, sizing, controlling, optimization, validation, marketing, sales, O&M, etc.
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An Input Linearized Powertrain Model for the Optimal Control of Hybrid Electric Vehicles. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0741.

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Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form. The output non-linearities can be approximated using a quadratic model, which creates a problem in the linear-quadratic framework. This facilitates the direct application of linear control approaches such as LQR control, predictive control, or Model Predictive Control (MPC). The paper demonstrates the approach using the ELectrified Vehicle library for sImulation and Optimization (ELVIO). It is an open-source MATLAB/Simulink library designed for the quick and easy simulation and optimization of different powertrain and drivetrain architectures. It follows a modelling methodology that combines backward-facing and forward-facing signal path, which means that no driver model is required. The results show that the approximated solution provides a performance that is very close to the solution of the original problem except for extreme parts of the operating range (in which case the solution tends to be driven by constraints anyway).
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