Developing an aCe solution for two-dimensional strip packing
Summary form only given. This paper describes the development of a fine-grained meta-heuristic for solving large strip packing problems with guillotine layouts. An architecture-adaptive environment aCe, and the aCe C parallel programming language are used to implement a massively parallel genetic si...
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| creator | Dorband, J.E. Mumford, C.L. Wang, P.Y. |
| description | Summary form only given. This paper describes the development of a fine-grained meta-heuristic for solving large strip packing problems with guillotine layouts. An architecture-adaptive environment aCe, and the aCe C parallel programming language are used to implement a massively parallel genetic simulated annealing (GSA) algorithm. The parallel GSA combines the temperature schedule of simulated annealing with the crossover and mutation operators that are applied to chromosome populations in genetic algorithms. For our problem, chromosomes are normalized postfix expressions that represent guillotine strip packings. Preliminary results for some benchmark data sets are reported and indicate that the parallel GSA method holds promise as a technique for solving the strip packing problem. |
| doi_str_mv | 10.1109/IPDPS.2004.1303331 |
| format | Conference Proceeding |
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This paper describes the development of a fine-grained meta-heuristic for solving large strip packing problems with guillotine layouts. An architecture-adaptive environment aCe, and the aCe C parallel programming language are used to implement a massively parallel genetic simulated annealing (GSA) algorithm. The parallel GSA combines the temperature schedule of simulated annealing with the crossover and mutation operators that are applied to chromosome populations in genetic algorithms. For our problem, chromosomes are normalized postfix expressions that represent guillotine strip packings. 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This paper describes the development of a fine-grained meta-heuristic for solving large strip packing problems with guillotine layouts. An architecture-adaptive environment aCe, and the aCe C parallel programming language are used to implement a massively parallel genetic simulated annealing (GSA) algorithm. The parallel GSA combines the temperature schedule of simulated annealing with the crossover and mutation operators that are applied to chromosome populations in genetic algorithms. For our problem, chromosomes are normalized postfix expressions that represent guillotine strip packings. Preliminary results for some benchmark data sets are reported and indicate that the parallel GSA method holds promise as a technique for solving the strip packing problem.</description><subject>Biological cells</subject><subject>Computer science</subject><subject>Genetics</subject><subject>NASA</subject><subject>Parallel programming</subject><subject>Programming profession</subject><subject>Simulated annealing</subject><subject>Strips</subject><subject>Temperature</subject><subject>Yarn</subject><isbn>0769521320</isbn><isbn>9780769521329</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jssKwjAURAMi-OoP6CY_0HrTpJaCu1bRXUH3JeitRNMkJFXx7-3CtbMZOMOBIWTJIGEMivWxrupTkgKIhHHgnLMRmUG-KbKU8RQmJArhDkOEyESeTcm2whdq65S5UWmoLJEGq5-9soa21tP-beOr6tCEgUhNQ--Vo05eHoOxIONW6oDRr-dktd-dy0OsELFxXnXSf5rfEf5__QLxJTeW</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Dorband, J.E.</creator><creator>Mumford, C.L.</creator><creator>Wang, P.Y.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2004</creationdate><title>Developing an aCe solution for two-dimensional strip packing</title><author>Dorband, J.E. ; Mumford, C.L. ; Wang, P.Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_13033313</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Biological cells</topic><topic>Computer science</topic><topic>Genetics</topic><topic>NASA</topic><topic>Parallel programming</topic><topic>Programming profession</topic><topic>Simulated annealing</topic><topic>Strips</topic><topic>Temperature</topic><topic>Yarn</topic><toplevel>online_resources</toplevel><creatorcontrib>Dorband, J.E.</creatorcontrib><creatorcontrib>Mumford, C.L.</creatorcontrib><creatorcontrib>Wang, P.Y.</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>Dorband, J.E.</au><au>Mumford, C.L.</au><au>Wang, P.Y.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Developing an aCe solution for two-dimensional strip packing</atitle><btitle>18th International Parallel and Distributed Processing Symposium, 2004. Proceedings</btitle><stitle>IPDPS</stitle><date>2004</date><risdate>2004</risdate><spage>261</spage><pages>261-</pages><isbn>0769521320</isbn><isbn>9780769521329</isbn><abstract>Summary form only given. This paper describes the development of a fine-grained meta-heuristic for solving large strip packing problems with guillotine layouts. An architecture-adaptive environment aCe, and the aCe C parallel programming language are used to implement a massively parallel genetic simulated annealing (GSA) algorithm. The parallel GSA combines the temperature schedule of simulated annealing with the crossover and mutation operators that are applied to chromosome populations in genetic algorithms. For our problem, chromosomes are normalized postfix expressions that represent guillotine strip packings. Preliminary results for some benchmark data sets are reported and indicate that the parallel GSA method holds promise as a technique for solving the strip packing problem.</abstract><pub>IEEE</pub><doi>10.1109/IPDPS.2004.1303331</doi></addata></record> |
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| ispartof | 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings, 2004, p.261 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biological cells Computer science Genetics NASA Parallel programming Programming profession Simulated annealing Strips Temperature Yarn |
| title | Developing an aCe solution for two-dimensional strip packing |
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