A Multi-Criteria Interval Optimization Model for Manufacturing Supplier Selection Using Genetic Algorithm
This paper presents a multi-criteria interval optimization model to determine the optimal criteria values and then rank the candidate suppliers. Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclid...
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| creator | Cheng, Fangqi Wang, Huaiao Ye, Feifan |
| description | This paper presents a multi-criteria interval optimization model to determine the optimal criteria values and then rank the candidate suppliers. Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclidean distance and vector theories. It is proved that the optimization objective function must have an optimal solution and genetic algorithm based on integer encoding is applied to obtain it. The computational results of a practical example suggested the proposed model and approach is satisfactory and the final choice is obtained. Finally, encouraging conclusions are given. |
| doi_str_mv | 10.1109/ETCS.2009.705 |
| format | Conference Proceeding |
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Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclidean distance and vector theories. It is proved that the optimization objective function must have an optimal solution and genetic algorithm based on integer encoding is applied to obtain it. The computational results of a practical example suggested the proposed model and approach is satisfactory and the final choice is obtained. 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Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclidean distance and vector theories. It is proved that the optimization objective function must have an optimal solution and genetic algorithm based on integer encoding is applied to obtain it. The computational results of a practical example suggested the proposed model and approach is satisfactory and the final choice is obtained. Finally, encouraging conclusions are given.</description><subject>Computer science education</subject><subject>Costs</subject><subject>Educational technology</subject><subject>Euclidean distance</subject><subject>genetic algorithm</subject><subject>Genetic algorithms</subject><subject>interval optimization</subject><subject>Manufacturing processes</subject><subject>Mathematical model</subject><subject>Paper technology</subject><subject>Pulp manufacturing</subject><subject>supplier selection</subject><subject>Virtual manufacturing</subject><isbn>1424435811</isbn><isbn>9781424435814</isbn><isbn>0769535577</isbn><isbn>9780769535579</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotUEtLAzEYDIigrT168pI_sDXP3eRYitZCSw-155LufqmfpLtLNivorzc-5jIwMwzDEHLP2ZxzZh-fXpf7uWDMziumr8iEK6GU1IbzazLJurFKlEbekNkwvLMMpaUy-pbggm7HkLBYRkwQ0dF1m_nDBbrrE17wyyXsWrrtGgjUd5FuXTt6V6cxYnum-7HvA0KkewhQ_0YPw4-xghYS1nQRzl2ufrvckWvvwgCzf56Sw3Oe_VJsdqv1crEpkFc6FXmWcLby3jhd-kZaViuo2Am8kScnrNDeVcLIqhaNdNKWtbWqMaW3XDeghZySh79eBIBjH_Hi4udRWZ0vEPIbWblYPg</recordid><startdate>200903</startdate><enddate>200903</enddate><creator>Cheng, Fangqi</creator><creator>Wang, Huaiao</creator><creator>Ye, Feifan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200903</creationdate><title>A Multi-Criteria Interval Optimization Model for Manufacturing Supplier Selection Using Genetic Algorithm</title><author>Cheng, Fangqi ; Wang, Huaiao ; Ye, Feifan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-3482a97ff8a56fd390c4e70bef83ba2925fa72837c2d3a396c994d86f915de523</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Computer science education</topic><topic>Costs</topic><topic>Educational technology</topic><topic>Euclidean distance</topic><topic>genetic algorithm</topic><topic>Genetic algorithms</topic><topic>interval optimization</topic><topic>Manufacturing processes</topic><topic>Mathematical model</topic><topic>Paper technology</topic><topic>Pulp manufacturing</topic><topic>supplier selection</topic><topic>Virtual manufacturing</topic><toplevel>online_resources</toplevel><creatorcontrib>Cheng, Fangqi</creatorcontrib><creatorcontrib>Wang, Huaiao</creatorcontrib><creatorcontrib>Ye, Feifan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cheng, Fangqi</au><au>Wang, Huaiao</au><au>Ye, Feifan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Multi-Criteria Interval Optimization Model for Manufacturing Supplier Selection Using Genetic Algorithm</atitle><btitle>2009 First International Workshop on Education Technology and Computer Science</btitle><stitle>ETCS</stitle><date>2009-03</date><risdate>2009</risdate><volume>3</volume><spage>757</spage><epage>761</epage><pages>757-761</pages><isbn>1424435811</isbn><isbn>9781424435814</isbn><isbn>0769535577</isbn><isbn>9780769535579</isbn><abstract>This paper presents a multi-criteria interval optimization model to determine the optimal criteria values and then rank the candidate suppliers. Evaluation criteria values are considered as interval data and the optimization model is constructed based on the concept of distance measure of the Euclidean distance and vector theories. It is proved that the optimization objective function must have an optimal solution and genetic algorithm based on integer encoding is applied to obtain it. The computational results of a practical example suggested the proposed model and approach is satisfactory and the final choice is obtained. Finally, encouraging conclusions are given.</abstract><pub>IEEE</pub><doi>10.1109/ETCS.2009.705</doi><tpages>5</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computer science education Costs Educational technology Euclidean distance genetic algorithm Genetic algorithms interval optimization Manufacturing processes Mathematical model Paper technology Pulp manufacturing supplier selection Virtual manufacturing |
| title | A Multi-Criteria Interval Optimization Model for Manufacturing Supplier Selection Using Genetic Algorithm |
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