Parametrical mechanical design with constraints and preferences: application to a purge valve
In the design of mechanical structures, the evolutionary algorithms have taken a more and more important place, mostly because of their ability to explore widely the design space. Furthermore, as several objectives are often pursued simultaneously in industrial applications, multiobjective optimizat...
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Veröffentlicht in: | Computer methods in applied mechanics and engineering 2003-09, Vol.192 (39), p.4355-4378 |
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creator | Coelho, R.Filomeno Bersini, H. Bouillard, Ph |
description | In the design of mechanical structures, the evolutionary algorithms have taken a more and more important place, mostly because of their ability to explore widely the design space. Furthermore, as several objectives are often pursued simultaneously in industrial applications, multiobjective optimization has become a wide area of research in recent years. However, only a few methods integrate a multicriteria decision aid approach to reflect the user’s preferences since the beginning of the search process. In this paper, PROMETHEE II, an outranking method developed in the operational research field, has been implemented in an evolutionary algorithm. Furthermore, as the handling of the constraints is very critical, an original technique called PAMUC (
Preferences Applied to MUltiobjectivity and Constraints) is proposed to tackle simultaneously the constrained and multiobjective aspects. It has been validated on standard test cases, and applied to the design optimization of two valves of the Vinci engine (from launcher Ariane 5). Results analyzed thanks to the R1 norm introduced by Hansen and Jaszkiewicz show that PAMUC outperforms the classical weighted-sum method (combined with a dynamic penalty-based technique to handle the constraints), and therefore seem to be more appropriate to reflect the user’s preferences. |
doi_str_mv | 10.1016/S0045-7825(03)00418-3 |
format | Article |
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Preferences Applied to MUltiobjectivity and Constraints) is proposed to tackle simultaneously the constrained and multiobjective aspects. It has been validated on standard test cases, and applied to the design optimization of two valves of the Vinci engine (from launcher Ariane 5). Results analyzed thanks to the R1 norm introduced by Hansen and Jaszkiewicz show that PAMUC outperforms the classical weighted-sum method (combined with a dynamic penalty-based technique to handle the constraints), and therefore seem to be more appropriate to reflect the user’s preferences.</description><identifier>ISSN: 0045-7825</identifier><identifier>EISSN: 1879-2138</identifier><identifier>DOI: 10.1016/S0045-7825(03)00418-3</identifier><identifier>CODEN: CMMECC</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Applied sciences ; Artificial intelligence ; Computational techniques ; Computer aided design ; Computer science; control theory; systems ; Constraints ; Design optimization ; Evolutionary algorithms ; Exact sciences and technology ; Learning and adaptive systems ; Mathematical methods in physics ; Mechanical engineering. Machine design ; Multicriteria ; Multiobjective ; Physics ; Pipings, valves, fittings ; Software ; Steel design</subject><ispartof>Computer methods in applied mechanics and engineering, 2003-09, Vol.192 (39), p.4355-4378</ispartof><rights>2003 Elsevier B.V.</rights><rights>2003 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-5fea9b6fd7b97ccd829a7b6c6d798742dce3f308a557238fec322988942db2273</citedby><cites>FETCH-LOGICAL-c368t-5fea9b6fd7b97ccd829a7b6c6d798742dce3f308a557238fec322988942db2273</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0045782503004183$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15080620$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Coelho, R.Filomeno</creatorcontrib><creatorcontrib>Bersini, H.</creatorcontrib><creatorcontrib>Bouillard, Ph</creatorcontrib><title>Parametrical mechanical design with constraints and preferences: application to a purge valve</title><title>Computer methods in applied mechanics and engineering</title><description>In the design of mechanical structures, the evolutionary algorithms have taken a more and more important place, mostly because of their ability to explore widely the design space. Furthermore, as several objectives are often pursued simultaneously in industrial applications, multiobjective optimization has become a wide area of research in recent years. However, only a few methods integrate a multicriteria decision aid approach to reflect the user’s preferences since the beginning of the search process. In this paper, PROMETHEE II, an outranking method developed in the operational research field, has been implemented in an evolutionary algorithm. Furthermore, as the handling of the constraints is very critical, an original technique called PAMUC (
Preferences Applied to MUltiobjectivity and Constraints) is proposed to tackle simultaneously the constrained and multiobjective aspects. It has been validated on standard test cases, and applied to the design optimization of two valves of the Vinci engine (from launcher Ariane 5). 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Machine design</topic><topic>Multicriteria</topic><topic>Multiobjective</topic><topic>Physics</topic><topic>Pipings, valves, fittings</topic><topic>Software</topic><topic>Steel design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Coelho, R.Filomeno</creatorcontrib><creatorcontrib>Bersini, H.</creatorcontrib><creatorcontrib>Bouillard, Ph</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computer methods in applied mechanics and engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Coelho, R.Filomeno</au><au>Bersini, H.</au><au>Bouillard, Ph</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parametrical mechanical design with constraints and preferences: application to a purge valve</atitle><jtitle>Computer methods in applied mechanics and engineering</jtitle><date>2003-09-26</date><risdate>2003</risdate><volume>192</volume><issue>39</issue><spage>4355</spage><epage>4378</epage><pages>4355-4378</pages><issn>0045-7825</issn><eissn>1879-2138</eissn><coden>CMMECC</coden><abstract>In the design of mechanical structures, the evolutionary algorithms have taken a more and more important place, mostly because of their ability to explore widely the design space. 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Preferences Applied to MUltiobjectivity and Constraints) is proposed to tackle simultaneously the constrained and multiobjective aspects. It has been validated on standard test cases, and applied to the design optimization of two valves of the Vinci engine (from launcher Ariane 5). Results analyzed thanks to the R1 norm introduced by Hansen and Jaszkiewicz show that PAMUC outperforms the classical weighted-sum method (combined with a dynamic penalty-based technique to handle the constraints), and therefore seem to be more appropriate to reflect the user’s preferences.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0045-7825(03)00418-3</doi><tpages>24</tpages></addata></record> |
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subjects | Applied sciences Artificial intelligence Computational techniques Computer aided design Computer science control theory systems Constraints Design optimization Evolutionary algorithms Exact sciences and technology Learning and adaptive systems Mathematical methods in physics Mechanical engineering. Machine design Multicriteria Multiobjective Physics Pipings, valves, fittings Software Steel design |
title | Parametrical mechanical design with constraints and preferences: application to a purge valve |
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