Relevant bibliographies by topics / Multi-objective methodology

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Multi-objective methodology'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Multi-objective methodology"

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Mohamed, Nejlaoui, Najlawi Bilel, and Ali Sulaiman Alsagri. "A multi-objective methodology for multi-criteria engineering design." Applied Soft Computing 91 (June 2020): 106204. http://dx.doi.org/10.1016/j.asoc.2020.106204.

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Frank, Christopher P., Renaud A. Marlier, Olivia J. Pinon-Fischer, and Dimitri N. Mavris. "Evolutionary multi-objective multi-architecture design space exploration methodology." Optimization and Engineering 19, no. 2 (2018): 359–81. http://dx.doi.org/10.1007/s11081-018-9373-x.

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Moselhi, Osama, and Nazila Roofigari-Esfahan. "Project schedule compression: a multi-objective methodology." Construction Innovation 13, no. 4 (2013): 374–93. http://dx.doi.org/10.1108/ci-03-2011-0010.

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Lin, Chuang, Jiwei Huang, Ying Chen, and Laizhong Cui. "Thinking and methodology of multi-objective optimization." International Journal of Machine Learning and Cybernetics 9, no. 12 (2018): 2117–27. http://dx.doi.org/10.1007/s13042-018-0866-x.

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Cuco, Ana Paula Curty, Fabiano L. de Sousa, and Antônio J. Silva Neto. "A multi-objective methodology for spacecraft equipment layouts." Optimization and Engineering 16, no. 1 (2014): 165–81. http://dx.doi.org/10.1007/s11081-014-9252-z.

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Priyadarshini, Manisha, Ajit Behera, Chandan Kumar Biswas, Biswajit Swain, and Swadhin Patel. "Multi-objective optimization of WEDM process by hybrid methodology." Materials Today: Proceedings 33 (2020): 5511–13. http://dx.doi.org/10.1016/j.matpr.2020.03.321.

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Harkouss, Fatima, Farouk Fardoun, and Pascal Henry Biwole. "Multi-objective optimization methodology for net zero energy buildings." Journal of Building Engineering 16 (March 2018): 57–71. http://dx.doi.org/10.1016/j.jobe.2017.12.003.

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Yao, Shiqing, Zhibin Jiang, Na Li, Na Geng, and Xiao Liu. "A decentralised multi-objective scheduling methodology for semiconductor manufacturing." International Journal of Production Research 49, no. 24 (2011): 7227–52. http://dx.doi.org/10.1080/00207543.2010.535040.

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Shea, John E., and Thomas M. West. "A methodology for curriculum development using multi-objective programming." Computers & Industrial Engineering 31, no. 1-2 (1996): 25–28. http://dx.doi.org/10.1016/0360-8352(96)00070-8.

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Teleb, Radi, and Farhad Azadivar. "A methodology for solvng multi-objective simulation-optimization problems." European Journal of Operational Research 72, no. 1 (1994): 135–45. http://dx.doi.org/10.1016/0377-2217(94)90336-0.

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Dissertations / Theses on the topic "Multi-objective methodology"

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Costa, Marco <1976&gt. "A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5688/.

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DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.
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Anagnostakis, Ioannis. "A multi-objective, decomposition-based algorithm design methodology and its application to runaway operations planning." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28913.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.<br>Includes bibliographical references (p. 283-296).<br>(cont.) to the design of a heuristic decomposed algorithm for solving the ROP problem. This decomposition methodology offers an original paradigm potentially applicable to the design of solution algorithms for a class of problems with functions and parameters that, similar to those of the ROP problem, can be parsed in subsets. The potential merit in decomposing the ROP problem in two stages and the resulting utility of the two-stage solution algorithm are evaluated by performing benefits analysis across specific dimensions related to airport efficiency, as well as stability and robustness analysis of the algorithm output.<br>Significant delays and resulting environmental impacts are commonly observed during departure operations at major US and European airports. One approach for mitigating airport congestion and delays is to exercise tactical operations planning and control with an objective to improve the efficiency of surface and terminal area operations. As a subtask of planning airport surface operations, this thesis presents a thorough study of the structure and properties of the Runway Operations Planning (ROP) problem. Runway Operations Planning is a workload-intensive task for controllers because airport operations involve many parameters, such as departure demand level and timing that are typically characterized by a highly dynamic behavior. This research work provides insight to the nature of this task, by analyzing the different parameters involved in it and illuminating how they interact with each other and how they affect the main functions in the problem of planning operations at the runway, such as departure runway throughput and runway queuing delays. Analysis of the Runway Operations Planning problem revealed that there is a parameter of the problem, namely the demand "weight class mix", which: a) is more "dominant" on the problem performance functions that other parameters, b) changes value much slower than other parameters and c) its value is available earlier and with more certainty than the value of other parameters. These observations enabled the parsing of the set of functions and the set of parameters in subsets, so that the problem can be addressed sequentially in more than one stage where different parameter subsets are treated in different stages. Thus, a decomposition-based algorithm design technique was introduced and applied<br>by Ioannis D. Anagnostakis.<br>Ph.D.
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Trifković, Aleksandar. "Multi-objective and risk-based modelling methodology for planning, design and operation of water supply systems." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-32516.

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Zhang, Zijun. "Wind turbine vibration study: a data driven methodology." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/454.

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Vibrations of a wind turbine have a negative impact on its performance and therefore approaches to effectively control turbine vibrations are sought by wind industry. The body of previous research on wind turbine vibrations has focused on physics-based models. Such models come with limitations as some ideal assumptions do not reflect reality. In this Thesis a data-driven approach to analyze the wind turbine vibrations is introduced. Improvements in the data collection of information system allow collection of large volumes of industrial process data. Although the sufficient information is contained in collected data, they cannot be fully utilized to solve the challenging industrial modeling issues. Data-mining is a novel science offers platform to identify models or recognize patterns from large data set. Various successful applications of data mining proved its capability in extracting models accurately describing the processes of interest. The vibrations of a wind turbine originate at various sources. This Thesis focuses on mitigating vibrations with wind turbine control. Data mining algorithms are utilized to construct vibration models of a wind turbine that are represented by two parameters, drive train acceleration and tower acceleration. An evolutionary strategy algorithm is employed to optimize the wind turbine performance expressed with three objectives, power generation, vibration of wind turbine drive train, and vibration of wind turbine tower. The methodology presented in this Thesis is applicable to industrial processes other than wind industry.
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Monteagudo, Maykel Cruz. "Multi-Objective Optimization Based on Desirability Estimation of Several Interrelated Responses (MOOp-DESIRe): A Computer-Aided Methodology for Multi-Criteria Drug Discovery." Tese, Faculdade de Farmácia da Universidade do Porto, 2009. http://hdl.handle.net/10216/63799.

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Monteagudo, Maykel Cruz. "Multi-Objective Optimization Based on Desirability Estimation of Several Interrelated Responses (MOOp-DESIRe): A Computer-Aided Methodology for Multi-Criteria Drug Discovery." Doctoral thesis, Faculdade de Farmácia da Universidade do Porto, 2009. http://hdl.handle.net/10216/63799.

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Trifković, Aleksandar [Verfasser]. "Multi-objective and risk-based modelling methodology for planning, design and operation of water supply systems / von Aleksandar Trifković." Stuttgart : Inst. für Wasserbau, 2007. http://d-nb.info/996789073/34.

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Bechara, Rami. "Methodology for the design of optimal processes : application to sugarcane conversion processes." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10229/document.

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L'adoption d'une méthodologie est cruciale pour la conception de procédés chimiques optimaux. L'optimisation multi-objective de modèles rigoureux en est un exemple, jouissant d'une application extensive dans la littérature. Cette méthode retourne un ensemble de solutions, dit de Pareto, présentant un compromis optimal entre les fonctions objectives. Ceci est suivi par une étape de sélection d'une solution d'intérêt répondant à des critères définis. Cette méthodologie s'appliquait, dans le cadre de cette thèse, à deux procédés. Le premier consistait en une distillerie d'éthanol à partir de la canne à sucre, combinée à un système de cogénération et de combustion à partir de la biomasse de canne à sucre. Le deuxième contenait en plus un système d'hydrolyse enzymatique de cette biomasse. Notre première contribution traitait de la construction d'une procédure pour la modélisation, simulation, intégration thermique et évaluation du coût des équipements. La deuxième contribution traitait de l'analyse des résultats réalisée à travers un suivi de variables mesurées, une fragmentation de la courbe de Pareto, une hiérarchisation des variables de décision et une comparaison avec la littérature. La dernière contribution traitait de l'étape de sélection qui s'est réalisée à travers une évaluation économique des solutions, sous des scénarii différents, avec la Valeur Nette Présente comme critère de sélection. En conclusion, cette thèse constitue une première application intégrale de la méthodologie proposée. Elle représente, de par ses contributions, un tremplin pour des applications futures à des procédés chimiques ou biochimiques, plus spécialement pour la canne à sucre<br>The use of a systematic methodology is crucial for the design of optimal chemical processes, namely bio-processes. Multi-objective optimization of rigorous process models is therein a prime example, with extensive use in literature. This method yields a Pareto set of optimal compromise solutions, from which one optimal solution is chosen based on specific criteria. This methodology was applied, in the course of this thesis, to two studied processes. The first consisted in a distillery converting sugarcane to ethanol, combined with a sugarcane biomass combustion and power cogeneration system. The second contained an additional biomass hydrolysis system. Our first contribution deals with the construction of an organized procedure for the modeling, simulation, heat integration and equipment and capital cost estimation of chemical processes. The second contribution deals with the analysis of the optimization results through a tracking of measured variables, the fragmentation of the Pareto curve, an ordering of optimization variables, and a comparisons with literature results. The final realization deals with the selection step realized through an economic evaluation of optimal solutions for various scenarios, with the Net Present Value as the selection criterion. In conclusion, this thesis constitutes a first integral application of the said methodology. It sets, through its contributions, a stepping stone for future application in the field of chemical and biochemical processes, namely for sugarcane processes
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Ordaz, Irian. "A probabilistic and multi-objective conceptual design methodology for the evaluation of thermal management systems on air-breathing hypersonic vehicles." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26478.

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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Mavris, Dimitri N.; Committee Member: German, Brian J.; Committee Member: Osburg, Jan; Committee Member: Ruffin, Stephen M.; Committee Member: Schrage, Daniel P.. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Escobar, Roberto Luiz. "Otimização de parametros de projeto de sistemas mecanicos atraves de algoritmo genetico multi-objetivos." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/264038.

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Orientador: Katia Lucchesi Cavalca<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-08T21:19:55Z (GMT). No. of bitstreams: 1 Escobar_RobertoLuiz_M.pdf: 2961640 bytes, checksum: 516985920427d6083c04c1c5a22d6470 (MD5) Previous issue date: 2007<br>Resumo: Os sistemas mecânicos são projetados para desempenhar funções específicas, e por essa razão as suas funções devem ser medidas para garantir seu desempenho dentro de uma certa precisão ou tolerância. A grande complexidade em se projetar e analisar novos projetos é a inserção de novas tecnologias, que envolvem aspectos multidisciplinares. Assim, o desenvolvimento e melhoria de projetos e produtos colocam o engenheiro projetista frente às diversas fontes de variabilidade, como por exemplo, as propriedades dos materiais, condições operacionais e ambientais e incertezas nas suposições feitas sobre seu funcionamento. Em termos de modelagem matemática, as aproximações inerentes e hipóteses feitas durante a concepção do sistema, conduzem normalmente a diferentes respostas obtidas através de simulações e/ou medidas experimentais. Dessa forma, em uma fase anterior à modelagem matemática,durante a concepção do sistema ou produto, as aplicações de ferramentas estatísticas e métodos de otimização podem fornecer estimativas sobre faixas de valores ou valores ótimos para parâmetros significativos de projeto, dentro do espaço experimental estudado. Esse tipo de abordagem estatística teve sua fundamentação teórica durante as décadas de 20 e 30 por Fisher, com a aplicação da teoria estatística sob diversos aspectos, como por exemplo: testes de hipóteses, estimativa de parâmetros, seleção de modelos, planejamento experimental e, mais tarde, no controle e melhoria de processos e produtos. Assim, este trabalho propõe um procedimento de estudo e otimização, integrando a teoria de planejamento experimental, a metodologia da superfície de resposta e otimização multi-objetivos através de algoritmos genéticos, para se obter a otimização dos parâmetros de projeto de componentes mecânicos. Em específico, foram utilizados dados de um sistema rotor-mancal e o estudo implica em minimizar as amplitudes no domínio da freqüência. Outro objetivo deste trabalho, foi desenvolver um programa para otimização multi-objetivos através de algoritmos genéticos<br>Abstract: The mechanical systems are designed to be applied to any specific situations, and in this waytheir features should be measured to guarantee confidence to the systems. Their development and analysis expose the designer to a series of unknown parameters from several sources such as material properties, environmental and operational conditions. In terms of mathematical modeling, the inherent approximation and hypotheses made during system conception lead to different responses obtained by simulations and/or experimental measurements. So, in a previous phase of mathematical modeling, during the design analysis, the application of statistical tools and optimization methods is possible to estimate the values and/or ranges of the critical design parameters inside an experimental space. The connection between optimization and statistical data back at least to the early part of the 20th century and encompasses many aspects of applied and theoretical statistics, including hypothesis testing, parameter estimation, model selection, design of experiments and process and product control. So, this work proposes a link between theory of design of experiments, response surface methodology and multi-objective optimization using genetic algorithms, in order to optimize parameters for mechanical components. This study makes possible to verify the application of multi-objective optimization using genetic algorithms in design parameters and optimize them. A rotor-bearing system was used and amplitude in frequency domain was minimized. An experimental software for multi-objective optimization using genetic algorithm was developed.<br>Mestrado<br>Mecanica dos Sólidos e Projeto Mecanico<br>Mestre em Engenharia Mecânica
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Books on the topic "Multi-objective methodology"

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Nudtasomboon, Nudtapon. Methodology for the multi-objective, resource-constrained project scheduling problem. 1993.

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A prática pedagógica no processo de alfabetização e letramento no ensino regular e multisseriado. Editora Acadêmica Periodicojs, 2021. http://dx.doi.org/10.51249/hp03.2021.22.

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This study addresses the issue of literacy and literacy in the early years of elementary school, considering the classes with regular and multi-grade education, starting from an analysis of pedagogical practices developed in the classroom, with relevant aspects such as: initial education and continuing of teachers, relating to the practices carried out in the school environment and at work with literacy and literacy. The objective was to analyze which factors influence the development of pedagogical practices from the perspective of literacy and literacy in the early years of elementary school in regular and multi-grade classes in the city of Pombal-PB. The methodology used starts from a descriptive study with qualitative and quantitative approach, characterized as a field research and having as research instruments structured questionnaires with open and closed questions, in an attempt to get as close to the reality of the object of study as possible analysis and reflection of the collected data and the contribution of some authors on the aborted theme. It was found with field research that several factors influence the development of pedagogical practice, such as: lack of teacher training programs that contribute to the relationship between theory and practice, more effective family participation in school and organization of teaching. meet the needs of the teaching and learning process with smaller classes not organized in multi-grade education. It is hoped that the present study can contribute to important discussions about pedagogical practices focused on the teacher's work and the process of literacy and literacy, with influence on the academic environments, the pedagogical practice of teachers and the different contexts that involve actions turned on the teaching and learning process.
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Book chapters on the topic "Multi-objective methodology"

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Wierzbicki, Andrzej P. "Multi-Objective Modeling." In Model-Based Decision Support Methodology with Environmental Applications. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9552-0_6.

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Nakayama, H. "Interactive Multi-Objective Programming and its Applications." In Methodology, Implementation and Applications of Decision Support Systems. Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-2606-6_7.

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Wierzbicki, Andrzej P. "Multi-Objective and Reference Point Optimization Tools." In Model-Based Decision Support Methodology with Environmental Applications. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-015-9552-0_9.

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Janssen, R., and M. van Herwijnen. "A Multi Objective Decision Support System for Public Planning." In Methodology, Implementation and Applications of Decision Support Systems. Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-2606-6_4.

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Bernal-Agustín, José L., Rodolfo Dufo-López, Franklin Mendoza, and José A. Domínguez-Navarro. "Multi-Layer Methodology Applied to Multi-period and Multi-Objective Design of Power Distribution Systems." In Electrical Engineering and Control. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21765-4_126.

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Kovalerchuk, Boris, and Leonid Perlovsky. "Sensor Resource Management: Intelligent Multi-objective Modularized Optimization Methodology and Models." In Recent Advances in Computational Intelligence in Defense and Security. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26450-9_25.

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Lim, Dudy, Yew-Soon Ong, Meng-Hiot Lim, and Yaochu Jin. "Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty." In Studies in Computational Intelligence. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-49774-5_19.

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Santos, Sérgio F., Nikolaos G. Paterakis, and João P. S. Catalão. "New Multi-objective Decision Support Methodology to Solve Problems of Reconfiguration in the Electric Distribution Systems." In IFIP Advances in Information and Communication Technology. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16766-4_42.

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Fountas, N. A., N. M. Vaxevanidis, C. I. Stergiou, and R. Benhadj-Djilali. "A Multi-objective Tool Path Optimization Methodology for Sculptured Surfaces Based on Experimental Data and Heuristic Search." In Digital Manufacturing and Assembly Systems in Industry 4.0. CRC Press, 2019. http://dx.doi.org/10.1201/9780429464768-5.

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Devadasan, S. R., S. T. Kiruba Shankaran, A. K. Deepak Raj, R. Narain Krishna, and S. Hariharan. "Multi-objective Optimization of CNC Turning Parameters of Grey Cast Iron Using Response Surface Methodology and Genetic Algorithm." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9809-8_35.

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Conference papers on the topic "Multi-objective methodology"

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Phadte, Siddhant. "Vehicle layout optimization using multi-objective genetic algorithms." In 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET). IEEE, 2017. http://dx.doi.org/10.1109/icammaet.2017.8186624.

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Sinha, Kaushik. "Reliability-Based Multi-Objective Optimization Methodology for Engineering Systems." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95240.

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This paper presents a methodology for reliability-based multi-objective design optimization (RBMODO) of automotive body components under impact scenario. Conflicting design requirements arise as one tries, for example, to minimize structural mass while maximizing energy absorption of an automotive rail section under structural and occupant safety related performance measure constraints. Because deterministic optimum designs obtained without taking uncertainty into account could lead to unreliable designs, a reliability-based approach to design optimization is preferable using a Reliability-based design optimization method. Uncertainty quantification is performed using two methods: reliability based approach and robustness based approach. The technique employed here treats multiple objective functions separately without combining them in any form. A decision-making criterion is subsequently invoked to select the “best” subset of solutions from the obtained non-dominated Pareto optimal solutions. The pareto optimal set obtained in case are compared and contrasted and observations made comparing reliability based approach vis-a`-vis robustness based approach. Deterministic, reliability-based and robustness based multi-objective optimization solutions are compared.
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Cococcioni, Marco, Massimo Pappalardo, and Yaroslav D. Sergeyev. "Towards lexicographic multi-objective linear programming using grossone methodology." In NUMERICAL COMPUTATIONS: THEORY AND ALGORITHMS (NUMTA–2016): Proceedings of the 2nd International Conference “Numerical Computations: Theory and Algorithms”. Author(s), 2016. http://dx.doi.org/10.1063/1.4965404.

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Selcuklu, S. B., D. W. Coit, F. Felder, M. Rodgers, and N. Wattanapongsakorn. "A new methodology for solving multi-objective stochastic optimization problems with independent objective functions." In 2013 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2013. http://dx.doi.org/10.1109/ieem.2013.6962383.

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Chedid, R., S. Karaki, and A. Rifai. "A multi-objective design methodology for hybrid renewable energy systems." In 2005 IEEE Russia Power Tech. IEEE, 2005. http://dx.doi.org/10.1109/ptc.2005.4524339.

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Masson, Louis, and Yves Perriard. "Multi-objective optimisation methodology for self-sensing piezoelectric monomorph benders." In 2019 12th International Symposium on Linear Drives for Industry Applications (LDIA). IEEE, 2019. http://dx.doi.org/10.1109/ldia.2019.8771002.

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Palermo, G., C. Silvano, S. Valsecchi, and V. Zaccaria. "A system-level methodology for fast multi-objective design space exploration." In the 13th ACM Great Lakes Symposium. ACM Press, 2003. http://dx.doi.org/10.1145/764808.764833.

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De Caro, Fabrizio, Alfredo Vaccaro, and Domenico Villacci. "A Reliable Multi-Objective Methodology for Strategic Bidding of Wind Energy." In 2020 55th International Universities Power Engineering Conference (UPEC). IEEE, 2020. http://dx.doi.org/10.1109/upec49904.2020.9209833.

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VERMA, ASHWANI, and RAVINDRA K. "Artificial Microstructure Generation of DP590 steel using multi objective TLBO methodology." In Sixth International Conference on Advances in Mechanical and Robotics Engineering - AMRE 2017. Institute of Research Engineers and Doctors, 2017. http://dx.doi.org/10.15224/978-1-63248-140-5-38.

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Tarcan, Esin, and A. Kerim Kar. "An Axiomatic Design Approach to Multi-Objective Optimization." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25097.

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In this study, a methodology is suggested by applying axiomatic design theory to multi-objective optimization of engineering design problems. In axiomatic design, Semangularity (S) and Reangularity (R) are utilized to decide which design is better. However it is not used for optimization purpose. This proposed methodology is applied on two case studies, as theoretical and thermal system multi-criteria optimization problems. It is foreseen that this methodology will reduce the degree of coupling in design optimization.
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Reports on the topic "Multi-objective methodology"

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Kobayashi, Marcelo H. (HBCU) Development and Application of a Biologically Inspired Methodology for the Optimized, Multi-Disciplinary and Multi-Objective Design of Air Vehicles. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada584389.

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