Permutation flow shop scheduling: fuzzy particle swarm optimization approach
dc.contributor.author | Ling, S. | |
dc.contributor.author | Jiang, F. | |
dc.contributor.author | Chan, Kit Yan | |
dc.contributor.author | Nguyen, H. | |
dc.contributor.editor | Chin-Teng Lin | |
dc.contributor.editor | Yau-Huang Kuo | |
dc.date.accessioned | 2017-01-30T11:03:38Z | |
dc.date.available | 2017-01-30T11:03:38Z | |
dc.date.created | 2012-02-09T20:00:50Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Ling, S.H. and Jiang, F. and Chan, K.Y. and Nguyen, H.T. 2011. Permutation flow shop scheduling: fuzzy particle swarm optimization approach, in IEEE International Conference on Fuzzy Systems (FUZZ 2011), Jun 27-30 2011. Taipei, Taiwan: IEEE. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/7953 | |
dc.identifier.doi | 10.1109/FUZZY.2011.6007320 | |
dc.description.abstract |
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. | |
dc.publisher | IEEE | |
dc.subject | Flow shop scheduling | |
dc.subject | Fuzzy logic | |
dc.subject | Particle swarm optimization | |
dc.title | Permutation flow shop scheduling: fuzzy particle swarm optimization approach | |
dc.type | Conference Paper | |
dcterms.source.startPage | 572 | |
dcterms.source.endPage | 578 | |
dcterms.source.issn | 1098-7584 | |
dcterms.source.title | Proceedings of the IEEE international conference on fuzzy systems (FUZZ 2011) | |
dcterms.source.series | Proceedings of the IEEE international conference on fuzzy systems (FUZZ 2011) | |
dcterms.source.conference | IEEE International Conference on Fuzzy Systems (FUZZ 2011) | |
dcterms.source.conference-start-date | Jun 27 2011 | |
dcterms.source.conferencelocation | Taipei, Taiwan | |
dcterms.source.place | Taiwan | |
curtin.department | Digital Ecosystems and Business Intelligence Institute (DEBII) | |
curtin.accessStatus | Fulltext not available |