Article ID: | iaor20083038 |
Country: | United Kingdom |
Volume: | 34 |
Issue: | 10 |
Start Page Number: | 3099 |
End Page Number: | 3111 |
Publication Date: | Oct 2007 |
Journal: | Computers and Operations Research |
Authors: | Liao Ching-Jong, Tseng Chao-Tang, Luarn Pin |
Keywords: | heuristics |
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.