Scheduling of nonresumable jobs and flexible maintenance activities on a single machine to minimize makespan

This study addresses a single machine scheduling problem with periodic maintenance, where the machine is assumed to be stopped periodically for maintenance for a constant time w during the scheduling period. Meanwhile, the maintenance period [ u, v] is assumed to have been previously arranged and th...

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Veröffentlicht in:European journal of operational research Jg. 190; H. 1; S. 90 - 102
1. Verfasser: Chen, Jen-Shiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.10.2008
Elsevier
Elsevier Sequoia S.A
Schriftenreihe:European Journal of Operational Research
Schlagworte:
Applied sciences
Availability constraints
Exact sciences and technology
Heuristic
Integer programming
Inventory control, production control. Distribution
Job shops
Maintenance
Mathematical programming
Operational research and scientific management
Operational research. Management science
Production scheduling
Repair & maintenance
Scheduling
Scheduling, sequencing
Single machine
Studies
Integer programming
Scheduling
Maintenance
Availability constraints
Single machine
Heuristic
Availability
Task scheduling
Mixed integer programming
Makespan
Modeling
Workload
Mixed model
Heuristic method
Time constant
ISSN:0377-2217, 1872-6860
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Zusammenfassung:This study addresses a single machine scheduling problem with periodic maintenance, where the machine is assumed to be stopped periodically for maintenance for a constant time w during the scheduling period. Meanwhile, the maintenance period [ u, v] is assumed to have been previously arranged and the time w is assumed not to exceed the available maintenance period [ u, v] (i.e. w ⩽ v − u). The time u( v) is the earliest (latest) time at which the machine starts (stops) its maintenance. The objective is to minimize the makespan. Two mixed binary integer programming (BIP) models are provided for deriving the optimal solution. Additionally, an efficient heuristic is proposed for finding the near-optimal solution for large-sized problems. Finally, computational results are provided to demonstrate the efficiency of the models and the effectiveness of the heuristics. The mixed BIP model can optimally solve up to 100-job instances, while the average percentage error of the heuristic is below 1%.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2007.06.029