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Solving Biobjective Distributed Flow-Shop Scheduling Problems With Lot-Streaming Using an Improved Jaya Algorithm
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AI
DOI：10.1109/TCYB.2022.3164165.png)
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摘要
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A distributed flow-shop scheduling problem with lot-streaming that considers completion time and total energy consumption is addressed. It requires to optimally assign jobs to multiple distributed factories and, at the same time, sequence them. A biobjective mathematic model is first developed to describe the considered problem. Then, an improved Jaya algorithm is proposed to solve it. The Nawaz-Enscore-Ham (NEH) initializing rule, a job-factory assignment strategy, the improved strategies for makespan and energy efficiency are designed based on the problem's characteristic to improve the Jaya's performance. Finally, experiments are carried out on 120 instances of 12 scales. The performance of the improved strategies is verified. Comparisons and discussions show that the Jaya algorithm improved by the designed strategies is highly competitive for solving the considered problem with makespan and total energy consumption criteria.
Keyword:
Production facilities
Job shop scheduling
Mathematical models
Energy consumption
Indexes
Collaboration
Memetics
Flow-shop scheduling
Jaya algorithm
lot-streaming
makespan
total energy consumption
期刊
IF:
10.5
论文数:
1.1W
被引数:
5.0W
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