Ant colony optimization for multi-objective flow shop scheduling problem

Flow shop scheduling problem consists of scheduling given jobs with same order at all machines. The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, multi-objective approach for scheduling...

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Bibliographic Details
Published in:Computers & industrial engineering 2008-04, Vol.54 (3), p.411-420
Main Authors: Yagmahan, Betul, Yenisey, Mehmet Mutlu
Format: Article
Language:English
Subjects:
Algorithms
Ant colony optimization
Comparative analysis
Flow shop
Heuristic
Job shops
Multi-objective
Optimization algorithms
Production scheduling
Scheduling
Studies
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Summary:Flow shop scheduling problem consists of scheduling given jobs with same order at all machines. The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, multi-objective approach for scheduling to reduce the total scheduling cost is important. Hence, in this study, we consider the flow shop scheduling problem with multi-objectives of makespan, total flow time and total machine idle time. Ant colony optimization (ACO) algorithm is proposed to solve this problem which is known as NP-hard type. The proposed algorithm is compared with solution performance obtained by the existing multi-objective heuristics. As a result, computational results show that proposed algorithm is more effective and better than other methods compared.
ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2007.08.003