A new particle swarm optimization for the open shop scheduling problem

This paper presents a new particle swarm optimization (PSO) for the open shop scheduling problem. Compared with the original PSO, we modified the particle position representation using priorities, and the particle movement using an insert operator. We also implemented a modified parameterized active...

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Bibliographic Details
Published in:Computers & operations research 2008-10, Vol.35 (10), p.3243-3261
Main Authors: Sha, D.Y., Hsu, Cheng-Yu
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Job shops
Open shop scheduling
Operational research and scientific management
Operational research. Management science
Optimization algorithms
Particle swarm optimization
Production scheduling
Schedules
Scheduling, sequencing
Solutions
Studies
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Summary:This paper presents a new particle swarm optimization (PSO) for the open shop scheduling problem. Compared with the original PSO, we modified the particle position representation using priorities, and the particle movement using an insert operator. We also implemented a modified parameterized active schedule generation algorithm (mP-ASG) to decode a particle position into a schedule. In mP-ASG, we can reduce or increase the search area between non-delay schedules and active schedules by controlling the maximum delay time allowed. Furthermore, we hybridized our PSO with beam search. The computational results show that our PSO found many new best solutions of the unsolved problems.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2007.02.019