Multi-objective flexible job shop scheduling problem based on non-dominated genetic algorithm

Yang Yacong, Wang Aimin*, Ge Yan

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Aiming at the limitation of flexible job shop scheduling (JSP), a multi-objective optimization model of JSP is constructed, which takes the maximum completion time and delivery time as the objective function. Considering the actual inventory size of job shop, a non dominated genetic algorithm is proposed. Combined with the actual inventory and demand, the program is developed to verify the feasibility and effectiveness of the algorithm. The results show that the algorithm can meet the delivery time and the maximum completion time at the same time, considering the size of inventory and achieve satisfactory results.

源语言英语
主期刊名Proceedings - International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020
出版商Institute of Electrical and Electronics Engineers Inc.
260-263
页数4
ISBN(电子版)9781728182889
DOI
出版状态已出版 - 6月 2020
已对外发布
活动2020 International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020 - Tianjin, 中国
期限: 26 6月 202028 6月 2020

出版系列

姓名Proceedings - International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020

会议

会议2020 International Conference on Artificial Intelligence and Electromechanical Automation, AIEA 2020
国家/地区中国
Tianjin
时期26/06/2028/06/20

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