A discrete version of particle swarm optimization for flowshop scheduling problems

  • Authors:

  • Ching-Jong Liao; Chao-Tang Tseng;Pin Luarn

  • Affiliations:

  • Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan;Department of Business Administration, National Taiwan University of Science and Technology, Taipei, Taiwan;Department of Business Administration, National Taiwan University of Science and Technology, Taipei, Taiwan

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2007

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Abstract

Particle swarm optimization (PSO) is a novel metaheuristic inspired by the flocking behavior of birds. The applications of PSO to scheduling problems are extremely few. In this paper, we present a PSO algorithm, extended from discrete PSO, for flowshop scheduling. In the proposed algorithm, the particle and the velocity are redefined, and an efficient approach is developed to move a particle to the new sequence. To verify the proposed PSO algorithm, comparisons with a continuous PSO algorithm and two genetic algorithms are made. Computational results show that the proposed PSO algorithm is very competitive. Furthermore, we incorporate a local search scheme into the proposed algorithm, called PSO-LS. Computational results show that the local search can be really guided by PSO in our approach. Also, PSO-LS performs well in flowshop scheduling with total flow time criterion, but it requires more computation times.