Permutation flow shop scheduling: Fuzzy particle swarm optimization approach

Publication Type:
Conference Proceeding
IEEE International Conference on Fuzzy Systems, 2011, pp. 572 - 578
Issue Date:
Filename Description Size
Thumbnail2010003984OK.pdf Published version462.59 kB
Adobe PDF
Full metadata record
A fuzzy particle swarm optimization (PSO) for the minimization of makespan in permutation flow shop scheduling problem is presented in this paper. In the proposed fuzzy PSO, the inertia weight of PSO and the control parameter of the cross-mutated operation are determined by a set of fuzzy rules. To escape the local optimum, cross-mutated operation is introduced. In order to make PSO suitable for solving permutation flow shop scheduling problem, a roulette wheel mechanism is proposed to convert the continuous position values of particles to job permutations. Meanwhile, a swap-based local search for scheduling problem is designed for the local exploration on a discrete job permutation space. Flow shop benchmark functions are employed to evaluate the performance of the fuzzy PSO for flow shop scheduling problems and the results indicate that the algorithm performs better compared with existing hybrid PSO algorithms. © 2011 IEEE.
Please use this identifier to cite or link to this item: