Permutation flow shop scheduling: fuzzy particle swarm optimization approach
MetadataShow full item 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.
Showing items related by title, author, creator and subject.
Ling, S.; Jiang, F.; Nguyen, H.; Chan, Kit Yan (2011)This paper proposes a hybrid fuzzy logic-based particle swarm optimization (PSO) with cross-mutated operation method for the minimization of makespan in permutation flow shop scheduling problem. This problem is a typical ...
A Fuzzy-Based Genetic Algorithm for Social Welfare Maximization by Placement and Sizing of Static Synchronous Series CompensatorNabavi, S.; Masoum, Mohammad Sherkat; Kazemi, A. (2011)This article presents a fuzzy-based genetic algorithm to maximize total social welfare and alleviate congestion by placement and sizing of one static synchronous series compensator device, considering its investment cost ...
Chayantrakom, Kittisak (2009)Flows of fluids and solid particles through microchannels have a very wide range of applications in biological and medical science and engineering. Understanding the mechanism of microflows will help to improve the ...