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A cooperative co-evolutionary particle swarm optimiser based on a niche sharing scheme for the flow shop scheduling problem under uncertainty

Published online by Cambridge University Press:  04 September 2014

BIN JIAO  and
SHAOBIN YAN
BIN JIAO
Affiliation:
Electric School, Shanghai Dianji University, 690 Jiang Chuan Road, Min Hang District, Shanghai, China Email: binjiaocn@163.com
SHAOBIN YAN
Affiliation:
School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China Email: yshaobin123@sina.com
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Abstract

The flow shop scheduling problem based on ideal and precise conditions has been a focus of considerable research since the first easy scheduling problem was formulated. In reality, some uncertain factors always restrict the scheduling optimisation problem. In this paper, taking uncertain processing time as an example, we use generalised rough sets theory to transform the rough flow shop scheduling model into the precise scheduling model. We adopt a cooperative co-evolutionary particle swarm optimisation algorithm based on a niche sharing scheme (NCPSO) to minimise the makespan in comparison with the particle swarm optimiser (PSO) and co-evolution particle swarm optimiser (CPSO) algorithms. The new algorithm is characterised by a strengthening of the ability to reserve excellent particles and searching the optimal solution. Experimental results show that the new algorithm is more effective and efficient than the others.

Type
Paper
Information
Mathematical Structures in Computer Science , Volume 24 , Special Issue 5: Mathematical Method in Intelligent Computing and Automation , October 2014 , e240502
Copyright
Copyright © Cambridge University Press 2014 

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