Job shop scheduling with sequence dependent setup times to minimize makespan

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This paper deals with a general job shop scheduling problem characterized by reentrant work flows and sequence dependent setup times. We utilize the disjunctive graph representation of the job shop with the objective of the minimum makespan to capture the interactions between machines. For this representation, four two-phase heuristics are proposed. Also, we present a local improvement imbedded genetic algorithm which combines a genetic algorithm with an efficient local improvement procedure. A comparative study is conducted to examine the performance of these proposed algorithms. Significance: Scheduling problems encountered in real industrial settings tend to have complex problem structures such as sequence dependent setup times and reentrant work flows. The problem considered herein is a more general and realistic one than previous studies.
Publisher
University of Texas at El Paso
Issue Date
2003-12
Language
English
Article Type
Article; Proceedings Paper
Keywords

ALGORITHM

Citation

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING : THEORY APPLICATIONS AND PRACTICE, v.10, no.4, pp.455 - 461

ISSN
1072-4761
URI
http://hdl.handle.net/10203/80641
Appears in Collection
IE-Journal Papers(저널논문)
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