Mixed binary integer programming formulations for the reentrant job shop scheduling problem

This paper describes the development of mixed binary integer programming (BIP) formulations for the reentrant job shop scheduling problem. Based on an earlier classical job shop model developed by Manne and improved by Liao and You, this paper presents two extended BIP optimization formulations for...

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Veröffentlicht in:Computers & operations research Jg. 32; H. 5; S. 1197 - 1212
Hauptverfasser: Pan, Jason Chao-Hsien, Chen, Jen-Shiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.05.2005
Elsevier Science
Pergamon Press Inc
Schlagworte:
Applied sciences
Exact sciences and technology
Integer programming
Job shops
Mathematical programming
Operational research and scientific management
Operational research. Management science
Production scheduling
Reentrant job shops
Scheduling
Scheduling, sequencing
Studies
Integer programming
Scheduling
Reentrant job shops
Job shop
Task scheduling
Mixed integer programming
Workload
ISSN:0305-0548, 1873-765X, 0305-0548
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Zusammenfassung:This paper describes the development of mixed binary integer programming (BIP) formulations for the reentrant job shop scheduling problem. Based on an earlier classical job shop model developed by Manne and improved by Liao and You, this paper presents two extended BIP optimization formulations for the problem under consideration. In order to improve the solution speed of the BIP formulations, two layer division procedures are developed and incorporated in the corresponding models. Results of computational experiments, in which an average performance of these formulations is investigated, are also reported.
Bibliographie:SourceType-Scholarly Journals-1
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2003.10.004