Assembly Process Planning Using a Multi-objective Optimization Method
Assembly process planning is a multi-objective optimization problem. Aiming to deal with such a complex multi-objective optimization problem, a new Pareto-based multi-objective evolutionary algorithm with fuzzy evaluating method is constructed in this paper. The optimization model of assembly proces...
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| creator | Qin yong-fa Xu zhi-gang |
| description | Assembly process planning is a multi-objective optimization problem. Aiming to deal with such a complex multi-objective optimization problem, a new Pareto-based multi-objective evolutionary algorithm with fuzzy evaluating method is constructed in this paper. The optimization model of assembly process planning is established. Several key technology, such as Pareto optimal front, solution ranking method are described. A fuzzy evaluating method for Pareto optimal front is proposed, and GASA (hybrids genetic algorithms and simulated annealing algorithms) optimization strategy is applied in the proposed algorithms. A program, called MOGASA (multi-objective optimization program using GASA algorithms) is developed based on the algorithms to solve assembly process planning problem. A computation example is presented in the paper. |
| doi_str_mv | 10.1109/ICMA.2007.4303610 |
| format | Conference Proceeding |
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Aiming to deal with such a complex multi-objective optimization problem, a new Pareto-based multi-objective evolutionary algorithm with fuzzy evaluating method is constructed in this paper. The optimization model of assembly process planning is established. Several key technology, such as Pareto optimal front, solution ranking method are described. A fuzzy evaluating method for Pareto optimal front is proposed, and GASA (hybrids genetic algorithms and simulated annealing algorithms) optimization strategy is applied in the proposed algorithms. A program, called MOGASA (multi-objective optimization program using GASA algorithms) is developed based on the algorithms to solve assembly process planning problem. 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A computation example is presented in the paper.</description><subject>Assembly process planning</subject><subject>Automation</subject><subject>Design optimization</subject><subject>Evolutionary computation</subject><subject>Fuzzy evaluating</subject><subject>Genetic algorithms</subject><subject>Manufacturing</subject><subject>Mechatronics</subject><subject>Multi-objective evolutionary optimization</subject><subject>Optimization methods</subject><subject>Pareto optimal front</subject><subject>Pareto optimization</subject><subject>Process planning</subject><subject>Robotic assembly</subject><issn>2152-7431</issn><issn>2152-744X</issn><isbn>9781424408276</isbn><isbn>142440827X</isbn><isbn>9781424408283</isbn><isbn>1424408288</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2007</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkM1Kw0AUhcc_sNQ8gLjJCyTOzL3JTJYh1FpoaBcW3JVJcken5Kd0olCf3opF8CzO4fDBWRzG7gWPheDZ46Io81hyrmIEDqngFyzIlBYoEbmWGi7ZRIpERgrx9eofU-n1HwNxywLvd_wkyJIU9YTNcu-pq9pjuD4MNXkfrlvT965_Czf-x01YfrSji4ZqR_XoPilc7UfXuS8zuqEPSxrfh-aO3VjTegrOOWWbp9lL8RwtV_NFkS8jJ1QyRqiMlmCBJBAmZAmaJK0FZoBpJSoDouZNpuBUla0qk2hhtbGY1pZzjTVM2cPvriOi7f7gOnM4bs-nwDeNVlCU</recordid><startdate>200708</startdate><enddate>200708</enddate><creator>Qin yong-fa</creator><creator>Xu zhi-gang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200708</creationdate><title>Assembly Process Planning Using a Multi-objective Optimization Method</title><author>Qin yong-fa ; Xu zhi-gang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-47a823f3e23e45efe3d56c149346b1ba31c0d9733467fbba581f8af46cf0084c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Assembly process planning</topic><topic>Automation</topic><topic>Design optimization</topic><topic>Evolutionary computation</topic><topic>Fuzzy evaluating</topic><topic>Genetic algorithms</topic><topic>Manufacturing</topic><topic>Mechatronics</topic><topic>Multi-objective evolutionary optimization</topic><topic>Optimization methods</topic><topic>Pareto optimal front</topic><topic>Pareto optimization</topic><topic>Process planning</topic><topic>Robotic assembly</topic><toplevel>online_resources</toplevel><creatorcontrib>Qin yong-fa</creatorcontrib><creatorcontrib>Xu zhi-gang</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 Xplore</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>Qin yong-fa</au><au>Xu zhi-gang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Assembly Process Planning Using a Multi-objective Optimization Method</atitle><btitle>2007 International Conference on Mechatronics and Automation</btitle><stitle>ICMA</stitle><date>2007-08</date><risdate>2007</risdate><spage>593</spage><epage>598</epage><pages>593-598</pages><issn>2152-7431</issn><eissn>2152-744X</eissn><isbn>9781424408276</isbn><isbn>142440827X</isbn><eisbn>9781424408283</eisbn><eisbn>1424408288</eisbn><abstract>Assembly process planning is a multi-objective optimization problem. Aiming to deal with such a complex multi-objective optimization problem, a new Pareto-based multi-objective evolutionary algorithm with fuzzy evaluating method is constructed in this paper. The optimization model of assembly process planning is established. Several key technology, such as Pareto optimal front, solution ranking method are described. A fuzzy evaluating method for Pareto optimal front is proposed, and GASA (hybrids genetic algorithms and simulated annealing algorithms) optimization strategy is applied in the proposed algorithms. A program, called MOGASA (multi-objective optimization program using GASA algorithms) is developed based on the algorithms to solve assembly process planning problem. A computation example is presented in the paper.</abstract><pub>IEEE</pub><doi>10.1109/ICMA.2007.4303610</doi><tpages>6</tpages></addata></record> |
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| issn | 2152-7431 2152-744X |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Assembly process planning Automation Design optimization Evolutionary computation Fuzzy evaluating Genetic algorithms Manufacturing Mechatronics Multi-objective evolutionary optimization Optimization methods Pareto optimal front Pareto optimization Process planning Robotic assembly |
| title | Assembly Process Planning Using a Multi-objective Optimization Method |
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