Job shop scheduling with beam search
dc.citation.epage | 412 | en_US |
dc.citation.issueNumber | 2 | en_US |
dc.citation.spage | 390 | en_US |
dc.citation.volumeNumber | 118 | en_US |
dc.contributor.author | Sabuncuoglu I. | en_US |
dc.contributor.author | Bayiz, M. | en_US |
dc.date.accessioned | 2016-02-08T10:40:39Z | |
dc.date.available | 2016-02-08T10:40:39Z | |
dc.date.issued | 1999 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | Beam Search is a heuristic method for solving optimization problems. It is an adaptation of the branch and bound method in which only some nodes are evaluated in the search tree. At any level, only the promising nodes are kept for further branching and remaining nodes are pruned off permanently. In this paper, we develop a beam search based scheduling algorithm for the job shop problem. Both the makespan and mean tardiness are used as the performance measures. The proposed algorithm is also compared with other well known search methods and dispatching rules for a wide variety of problems. The results indicate that the beam search technique is a very competitive and promising tool which deserves further research in the scheduling literature. | en_US |
dc.identifier.doi | 10.1016/S0377-2217(98)00319-1 | en_US |
dc.identifier.issn | 0377-2217 | |
dc.identifier.uri | http://hdl.handle.net/11693/25191 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier Science B.V., Amsterdam, Netherlands | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/S0377-2217(98)00319-1 | en_US |
dc.source.title | European Journal of Operational Research | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Heuristic methods | en_US |
dc.subject | Industrial management | en_US |
dc.subject | Manufacture | en_US |
dc.subject | Operations research | en_US |
dc.subject | Optimization | en_US |
dc.subject | Beam search | en_US |
dc.subject | Job shop scheduling | en_US |
dc.subject | Scheduling | en_US |
dc.title | Job shop scheduling with beam search | en_US |
dc.type | Article | en_US |
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