A similar particle swarm optimization algorithm for permutation flowshop scheduling to minimize makespan

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摘要

The flow-shop scheduling problem (FSSP) is a branch of production scheduling, which is among the hardest combinatorial optimization problems. It is well known that this problem with current algorithms even moderately sized problems cannot be solved to guaranteed optimality. Many different approaches have been applied for permutation flowshop scheduling to minimize makespan, but these methods are not satisfying. Particle swarm optimization (PSO) has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper through the improvement of the option modes of gBest and pBest of PSO algorithm, a similar particle swarm optimization algorithm (SPSOA) applied for permutation flowshop scheduling to minimize makespan is firstly presented. The comparisons are made with SPSOAs and the standard GAs, in which we obtained that the SPSOAs are more clearly efficacious than standard GAs for FSSP to minimize makespan. Computational experiments show the efficiency of the proposed (SPSOA) solving approaches.

论文关键词:Flow-shop scheduling,Genetic algorithm,Particle swarm optimization,Similar particle swarm optimization algorithm (SPSOA),Crossover operators

论文评审过程:Available online 6 October 2005.

论文官网地址:https://doi.org/10.1016/j.amc.2005.07.042