Hybrid genetic algorithm for group technology economic lot scheduling problem
The concept of group technology has been successfully applied to many production systems, including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem, which has been studied for over 40 years. We develop a heuristic algorithm an...
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| Veröffentlicht in: | International journal of production research 2006-11, Vol.44 (21), p.4551-4568 |
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| container_end_page | 4568 |
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| container_issue | 21 |
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| container_title | International journal of production research |
| container_volume | 44 |
| creator | Moon, I. K. Cha, B. C. Bae, H. C. |
| description | The concept of group technology has been successfully applied to many production systems, including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem, which has been studied for over 40 years. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem. Numerical experiments show that the developed algorithms outperform the existing heuristics. |
| doi_str_mv | 10.1080/00207540500534405 |
| format | Article |
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K. ; Cha, B. C. ; Bae, H. C.</creator><creatorcontrib>Moon, I. K. ; Cha, B. C. ; Bae, H. C.</creatorcontrib><description>The concept of group technology has been successfully applied to many production systems, including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem, which has been studied for over 40 years. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem. 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K.</creatorcontrib><creatorcontrib>Cha, B. C.</creatorcontrib><creatorcontrib>Bae, H. C.</creatorcontrib><title>Hybrid genetic algorithm for group technology economic lot scheduling problem</title><title>International journal of production research</title><description>The concept of group technology has been successfully applied to many production systems, including flexible manufacturing systems. In this paper we apply group technology principles to the economic lot scheduling problem, which has been studied for over 40 years. We develop a heuristic algorithm and a hybrid genetic algorithm for the group technology economic lot scheduling problem. Numerical experiments show that the developed algorithms outperform the existing heuristics.</description><subject>Applied sciences</subject><subject>Economic lot scheduling problem</subject><subject>Exact sciences and technology</subject><subject>Genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Group technology</subject><subject>Heuristic</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Production scheduling</subject><subject>Scheduling algorithms</subject><subject>Scheduling, sequencing</subject><subject>Studies</subject><issn>0020-7543</issn><issn>1366-588X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNqFkM1q3DAURkVoIJNJH6A7U0h2bvVjWRJkE0LSKaRkk0B2QpavPR5kayrJtPP20TBTCg2k2tyFzvnu5UPoE8FfCJb4K8YUC15hjjFnVZ4naEFYXZdcypcPaLH_LzPAztB5jBucH5fVAv1Y7ZowtEUPE6TBFsb1PgxpPRadD0Uf_LwtEtj15J3vdwVYP_kxc86nIto1tLMbpr7YBt84GC_QaWdchI_HuUTP93dPt6vy4fHb99ubh9JWrEolrTvFK1rjihlhcWuhbXDLG4CuUp1Q3NDaig44GBBCqJZyaZuGUMHbGivJlujqkJv3_pwhJj0O0YJzZgI_R00VVYwRlsHP_4AbP4cp36YpkTWnipAMkQNkg48xQKe3YRhN2GmC9b5d_abd7Fweg020xnXBTHaIf0VJsFJyn3194IYpFzqaXz64Viezcz78kdh7a8R_9TeWTr8TewV88Z7q</recordid><startdate>20061101</startdate><enddate>20061101</enddate><creator>Moon, I. K.</creator><creator>Cha, B. C.</creator><creator>Bae, H. 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| ispartof | International journal of production research, 2006-11, Vol.44 (21), p.4551-4568 |
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| language | eng |
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| source | EBSCOhost Business Source Complete; Taylor & Francis Journals Complete |
| subjects | Applied sciences Economic lot scheduling problem Exact sciences and technology Genetic algorithm Genetic algorithms Group technology Heuristic Operational research and scientific management Operational research. Management science Production scheduling Scheduling algorithms Scheduling, sequencing Studies |
| title | Hybrid genetic algorithm for group technology economic lot scheduling problem |
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