Journal of System Simulation
Abstract
Abstract: In the synergic production scheduling optimization problem of distributed multi-plants, it is necessary to consider the two stages of job allocation between factories and job scheduling in factories at the same time. This paper first establishes a distributed multi-plant scheduling model with total cost and advance/delay as the optimization objectives, and then proposes a nested optimization algorithm framework integrating ID3 decision tree with Gauss particle swarm optimization. In this framework, independent scheduling optimization within the factory is nested in the process of inter factory allocation optimization, and elite retention strategy is introduced to improve the algorithm optimization. In addition, ID3 decision tree technology is integrated into the process of outer layer optimization particle generation to reduce the randomness of outer layer optimization. Simulation results show that the algorithm has advantages in optimization, convergence and CPU time.
Recommended Citation
Yan, Wang and Jiang, Tianlun
(2019)
"Synergic Production Scheduling Method for Distributed Multi-Plants Based on Fusion Decision Tree,"
Journal of System Simulation: Vol. 31:
Iss.
11, Article 1.
DOI: 10.16182/j.issn1004731x.joss. 19-0559
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol31/iss11/1
First Page
2181
Revised Date
2019-10-23
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss. 19-0559
Last Page
2197
CLC
TP18
Recommended Citation
Wang Yan, Jiang Tianlun. Synergic Production Scheduling Method for Distributed Multi-Plants Based on Fusion Decision Tree[J]. Journal of System Simulation, 2019, 31(11): 2181-2197.
DOI
10.16182/j.issn1004731x.joss. 19-0559
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