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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computer methods in applied mechanics and engineering 2003-09, Vol.192 (39), p.4355-4378
Hauptverfasser: Coelho, R.Filomeno, Bersini, H., Bouillard, Ph
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 4378
container_issue 39
container_start_page 4355
container_title Computer methods in applied mechanics and engineering
container_volume 192
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
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_27818161</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0045782503004183</els_id><sourcerecordid>27818161</sourcerecordid><originalsourceid>FETCH-LOGICAL-c368t-5fea9b6fd7b97ccd829a7b6c6d798742dce3f308a557238fec322988942db2273</originalsourceid><addsrcrecordid>eNqFkE1LxDAQhoMouH78BCEXRQ_VfNgm9SKy-AWCgnqUMJtONdJNa5Jd8d-b3RU9mksy5HlnmIeQPc6OOePVySNjp2WhtCgPmTzKBdeFXCMjrlVdCC71Ohn9IptkK8Z3lo_mYkReHiDAFFNwFjo6RfsGfvlsMLpXTz9deqO29zEFcD5FCr6hQ8AWA3qL8YzCMHQ5kVzvaeop0GEWXpHOoZvjDtlooYu4-3Nvk-ery6fxTXF3f307vrgrrKx0KsoWoZ5UbaMmtbK20aIGNals1ahaq1PRWJStZBrKUgmpW7RSiFrrOn9NhFBymxys-g6h_5hhTGbqosWuA4_9LBqhNNe84hksV6ANfYx5DTMEN4XwZTgzC5lmKdMsTBkmzVKmkTm3_zMAYrbTBvDWxb9wyTSrBMvc-YrDvO3cYTDRuoWoxgW0yTS9-2fSN1t9ifI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>27818161</pqid></control><display><type>article</type><title>Parametrical mechanical design with constraints and preferences: application to a purge valve</title><source>Elsevier ScienceDirect Journals</source><creator>Coelho, R.Filomeno ; Bersini, H. ; Bouillard, Ph</creator><creatorcontrib>Coelho, R.Filomeno ; Bersini, H. ; Bouillard, Ph</creatorcontrib><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.</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>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=15080620$$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). 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><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computational techniques</subject><subject>Computer aided design</subject><subject>Computer science; control theory; systems</subject><subject>Constraints</subject><subject>Design optimization</subject><subject>Evolutionary algorithms</subject><subject>Exact sciences and technology</subject><subject>Learning and adaptive systems</subject><subject>Mathematical methods in physics</subject><subject>Mechanical engineering. Machine design</subject><subject>Multicriteria</subject><subject>Multiobjective</subject><subject>Physics</subject><subject>Pipings, valves, fittings</subject><subject>Software</subject><subject>Steel design</subject><issn>0045-7825</issn><issn>1879-2138</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LxDAQhoMouH78BCEXRQ_VfNgm9SKy-AWCgnqUMJtONdJNa5Jd8d-b3RU9mksy5HlnmIeQPc6OOePVySNjp2WhtCgPmTzKBdeFXCMjrlVdCC71Ohn9IptkK8Z3lo_mYkReHiDAFFNwFjo6RfsGfvlsMLpXTz9deqO29zEFcD5FCr6hQ8AWA3qL8YzCMHQ5kVzvaeop0GEWXpHOoZvjDtlooYu4-3Nvk-ery6fxTXF3f307vrgrrKx0KsoWoZ5UbaMmtbK20aIGNals1ahaq1PRWJStZBrKUgmpW7RSiFrrOn9NhFBymxys-g6h_5hhTGbqosWuA4_9LBqhNNe84hksV6ANfYx5DTMEN4XwZTgzC5lmKdMsTBkmzVKmkTm3_zMAYrbTBvDWxb9wyTSrBMvc-YrDvO3cYTDRuoWoxgW0yTS9-2fSN1t9ifI</recordid><startdate>20030926</startdate><enddate>20030926</enddate><creator>Coelho, R.Filomeno</creator><creator>Bersini, H.</creator><creator>Bouillard, Ph</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20030926</creationdate><title>Parametrical mechanical design with constraints and preferences: application to a purge valve</title><author>Coelho, R.Filomeno ; Bersini, H. ; Bouillard, Ph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-5fea9b6fd7b97ccd829a7b6c6d798742dce3f308a557238fec322988942db2273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computational techniques</topic><topic>Computer aided design</topic><topic>Computer science; control theory; systems</topic><topic>Constraints</topic><topic>Design optimization</topic><topic>Evolutionary algorithms</topic><topic>Exact sciences and technology</topic><topic>Learning and adaptive systems</topic><topic>Mathematical methods in physics</topic><topic>Mechanical engineering. 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. 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.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0045-7825(03)00418-3</doi><tpages>24</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0045-7825
ispartof Computer methods in applied mechanics and engineering, 2003-09, Vol.192 (39), p.4355-4378
issn 0045-7825
1879-2138
language eng
recordid cdi_proquest_miscellaneous_27818161
source Elsevier ScienceDirect Journals
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
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-19T03%3A57%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Parametrical%20mechanical%20design%20with%20constraints%20and%20preferences:%20application%20to%20a%20purge%20valve&rft.jtitle=Computer%20methods%20in%20applied%20mechanics%20and%20engineering&rft.au=Coelho,%20R.Filomeno&rft.date=2003-09-26&rft.volume=192&rft.issue=39&rft.spage=4355&rft.epage=4378&rft.pages=4355-4378&rft.issn=0045-7825&rft.eissn=1879-2138&rft.coden=CMMECC&rft_id=info:doi/10.1016/S0045-7825(03)00418-3&rft_dat=%3Cproquest_cross%3E27818161%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=27818161&rft_id=info:pmid/&rft_els_id=S0045782503004183&rfr_iscdi=true