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An improved particle swarm optimization algorithm for flowshop scheduling problem

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4 Author(s)
Bo Li ; Comput. Center, Changchun Inst. of Technol., Changchun ; Changsheng Zhang ; Ge Bai ; Erliang Zhang

The flowshop scheduling problem has been widely studied in the literature and many techniques have been applied to it, but few algorithms have been proposed to solve it using particle swarm optimization algorithm (PSO) based algorithm. In this paper, an improved PSO algorithm (IPSO) based on the ldquoall differentrdquo constraint is proposed to solve the flowshop scheduling problem with the objective of minimizing makespan. It combines the particle swarm optimization algorithm with genetic operators together effectively. When a particle is going to stagnates, the mutation operator is used to search its neighborhood. The proposed algorithm is tested on different scale benchmarks and compared with the recently proposed efficient algorithms. The results show that both the solution quality and the convergent speed of the IPSO algorithm precede the other two recently proposed algorithms. It can be used to solve large scale flowshop scheduling problem effectively.

Published in:

Information and Automation, 2008. ICIA 2008. International Conference on

Date of Conference:

20-23 June 2008