Research on Composite Dispatching Rules of Assembly Job Shop Scheduling Based on Gene Expression Programming

被引：0
|
作者：
Lü H. [1 ,2 ,3 ]
Huang Z. [1 ,2 ,3 ]
Chen J. [1 ,2 ]
Wang Z. [1 ,2 ]
Wu S. [1 ,2 ]
Han G. [4 ]
机构：
[1] School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan
[2] Institute of Logistics System Science and Engineering, Wuhan University of Technology, Wuhan
[3] Ministry of Education Engineering Research Center for Port Logistics Technology and Equipment, Wuhan
[4] Wuhan Tianma Microelectronics Co., Ltd., Wuhan
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2023年 / 59卷 / 16期
关键词：
assembly job shop scheduling; dispatching rules; feature selection; gene expression programming;
D O I：
10.3901/JME.2023.16.427
中图分类号：
学科分类号：
摘要：
Dispatching rules is a simple and effective approach for job shop scheduling problems. Aiming at an assembly job shop scheduling problem(AJSP), a simulation model is established and a gene expression programming(GEP) algorithm is proposed to automatically generate and search optimal dispatching rules. Simulation results show that under the two optimization objectives of minimizing mean flow time and mean absolute deviation, the GEP algorithm can find better solutions than existing commonly used dispatching rules and shows advantages in computation time and solving quality, together with a certain level of robustness. Specifically, a feature selection scheme is designed to reduce the search space and improve search performance. A dynamic self-adaptive scheme is also applied to improve the search ability of GEP, and the effectiveness of the proposed algorithm is proved by simulating experiments constructed for different production environments. © 2023 Editorial Office of Chinese Journal of Mechanical Engineering. All rights reserved.
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页码：427 / 434
页数：7
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