Journal of System Simulation
Abstract
Abstract: For the uncertainty of parameters during flexible industrial process in the manufacturing workshops, a model of multi-objective fuzzy flexible job shop scheduling is established. To solve this model, the processing time, processing cost and material cost are described by triangular fuzzy numbers to minimize the makespan and production cost. An adaptive discrete flower pollination algorithm (ADMOFPA) is proposed. A discrete operator is utilized in the algorithm to discretize the solutions at the initialization period. To enhance the global exploration and local exploitation ability of ADMOFPA, an adaptive mutation operator is adopted. By simulating the instance of one flexible production workshop using the proposed algorithm, the results validate the effectiveness of the proposed algorithm compared with the basic FPA and particle swarm optimization.
Recommended Citation
Xu, Wenhao; Yan, Wang; Yan, Dahu; and Ji, Zhicheng
(2019)
"Flower Pollination Algorithm for Multi-Objective Fuzzy Flexible Job Shop Scheduling,"
Journal of System Simulation: Vol. 30:
Iss.
11, Article 42.
DOI: 10.16182/j.issn1004731x.joss.201811042
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss11/42
First Page
4403
Revised Date
2018-06-02
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201811042
Last Page
4412
CLC
TP278
Recommended Citation
Xu Wenhao, Wang Yan, Yan Dahu, Ji Zhicheng. Flower Pollination Algorithm for Multi-Objective Fuzzy Flexible Job Shop Scheduling[J]. Journal of System Simulation, 2018, 30(11): 4403-4412.
DOI
10.16182/j.issn1004731x.joss.201811042
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