Journal of System Simulation
Abstract
Abstract: According to the actual production situation of China's manufacturing industry, a hyperheuristic algorithm based on K-means clustering is proposed for inter-cell scheduling problem of flexible job-shop. K-means clustering is applied to group entities with similar attributes into the corresponding work cluster decision blocks, and the ant colony algorithm is used to select heuristic rules for each decision block. The optimal scheduling solutions are generated by using corresponding heuristic rules for scheduling of entities in each decision block. Computational results show that, the computational granularity is properly increased by the form of decision blocks, and the computational efficiency of the optimal algorithm is improved. The clustering algorithm could group the processed entities with similar attributes and the suitable rules for entities with different attributes are easy to be chosen. The proposed approach not only improves computational efficiency but also exhibits good optimization performance, and provides a scientific optimization solution for inter-cell scheduling problems.
Recommended Citation
Zhao, Yanlin and Tian, Yunna
(2024)
"Hyper-heuristic Approach with K-means Clustering for Inter-cell Scheduling,"
Journal of System Simulation: Vol. 36:
Iss.
4, Article 13.
DOI: 10.16182/j.issn1004731x.joss.22-1541
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss4/13
First Page
941
Last Page
956
CLC
TP18; TP301.6
Recommended Citation
Zhao Yanlin, Tian Yunna. Hyper-heuristic Approach with K-means Clustering for Inter-cell Scheduling [J]. Journal of System Simulation, 2024, 36(4): 941-956.
DOI
10.16182/j.issn1004731x.joss.22-1541
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