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Conference Paper: Machine requirements planning and workload assignment using genetic algorithms
Title | Machine requirements planning and workload assignment using genetic algorithms |
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Authors | |
Keywords | Computers Artificial intelligence |
Issue Date | 1995 |
Publisher | IEEE. |
Citation | Proceedings Of The Ieee Conference On Evolutionary Computation, 1995, v. 2, p. 711-715 How to Cite? |
Abstract | This paper presents a genetic approach to determining the optimal number of machines required in a manufacturing system for meeting a specified production schedule. This use of genetic algorithms is illustrated by solving a typical machine requirements planning problem. Comparison of the respective results obtained by using the proposed approach and a standard mixed-integer programming package shows that the proposed approach is indeed an effective means for optimal manufacturing systems design. |
Persistent Identifier | http://hdl.handle.net/10722/46570 |
DC Field | Value | Language |
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dc.contributor.author | Porter, B | en_HK |
dc.contributor.author | Mak, KL | en_HK |
dc.contributor.author | Wong, YS | en_HK |
dc.date.accessioned | 2007-10-30T06:53:09Z | - |
dc.date.available | 2007-10-30T06:53:09Z | - |
dc.date.issued | 1995 | en_HK |
dc.identifier.citation | Proceedings Of The Ieee Conference On Evolutionary Computation, 1995, v. 2, p. 711-715 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/46570 | - |
dc.description.abstract | This paper presents a genetic approach to determining the optimal number of machines required in a manufacturing system for meeting a specified production schedule. This use of genetic algorithms is illustrated by solving a typical machine requirements planning problem. Comparison of the respective results obtained by using the proposed approach and a standard mixed-integer programming package shows that the proposed approach is indeed an effective means for optimal manufacturing systems design. | en_HK |
dc.format.extent | 431222 bytes | - |
dc.format.extent | 4653 bytes | - |
dc.format.extent | 2656 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | text/plain | - |
dc.format.mimetype | text/plain | - |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.relation.ispartof | Proceedings of the IEEE Conference on Evolutionary Computation | en_HK |
dc.rights | ©1995 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Computers | en_HK |
dc.subject | Artificial intelligence | en_HK |
dc.title | Machine requirements planning and workload assignment using genetic algorithms | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Mak, KL:makkl@hkucc.hku.hk | en_HK |
dc.identifier.authority | Mak, KL=rp00154 | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.doi | 10.1109/ICEC.1995.487472 | en_HK |
dc.identifier.scopus | eid_2-s2.0-0029520855 | en_HK |
dc.identifier.hkuros | 20994 | - |
dc.identifier.volume | 2 | en_HK |
dc.identifier.spage | 711 | en_HK |
dc.identifier.epage | 715 | en_HK |
dc.identifier.scopusauthorid | Porter, B=7201565386 | en_HK |
dc.identifier.scopusauthorid | Mak, KL=7102680226 | en_HK |
dc.identifier.scopusauthorid | Wong, YS=26637607500 | en_HK |