Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이동호 | - |
dc.date.accessioned | 2018-04-16T02:17:13Z | - |
dc.date.available | 2018-04-16T02:17:13Z | - |
dc.date.issued | 2012-10 | - |
dc.identifier.citation | International journal of production research, 2012, 50(20), pp.6040 - 6057 | en_US |
dc.identifier.issn | 0020-7543 | - |
dc.identifier.uri | https://www.tandfonline.com/doi/abs/10.1080/00207543.2011.644591 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/67471 | - |
dc.description.abstract | This study considers common due-date assignment and scheduling on parallel machines. The problem has three decision variables: assigning the common-due-date, allocating jobs to parallel machines, and sequencing the jobs assigned to each machine. The objective is to minimise the sum of due-date assignment, earliness and tardiness penalties. A mathematical programming model is presented, and then two types of heuristics are suggested after characterising the optimal solution properties. The two types of heuristics are: (a) a fast two-stage heuristic with obtaining an initial solution and improvement; and (b) two meta-heuristics, tabu search and simulated annealing, with new neighbourhood generation methods. Computational experiments were conducted on a number of test instances, and the results show that each of the heuristic types outperforms the existing one. In particular, the meta-heuristics suggested in this study are significantly better than the existing genetic algorithm. | en_US |
dc.description.sponsorship | This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD, BasicResearch Promotion Fund) (KRF-2007-331-D00547). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.subject | parallel machine scheduling | en_US |
dc.subject | common due-date assignment | en_US |
dc.subject | fast heuristics | en_US |
dc.subject | meta-heuristics | en_US |
dc.title | Fast and meta-heuristics for common due-date assignment and scheduling on parallel machines | en_US |
dc.type | Article | en_US |
dc.relation.no | 20 | - |
dc.relation.volume | 50 | - |
dc.identifier.doi | 10.1080/00207543.2011.644591 | - |
dc.relation.page | 6040-6057 | - |
dc.relation.journal | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | - |
dc.contributor.googleauthor | Kim, J.-G. | - |
dc.contributor.googleauthor | Kim, J.-S. | - |
dc.contributor.googleauthor | Lee, D.-H. | - |
dc.relation.code | 2012204303 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF INDUSTRIAL ENGINEERING | - |
dc.identifier.pid | leman | - |
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