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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2025 Vol.26 No.3 P.332-353
A review of flexible job shop scheduling problems considering transportation vehicles
Abstract: The flexible job shop scheduling problem for processing machines and transportation vehicles (FJSP_PT) has garnered significant attention from academia and industry. Due to the inclusion of transportation vehicle scheduling in the scheduling problem of flexible manufacturing systems, solving FJSP_PT becomes more challenging and significantly more practically relevant compared to the flexible job shop scheduling problem. We summarize the assumptions, constraints, objective functions, and benchmarks of FJSP_PT. Then, statistical analysis is conducted on the literature up to 2023, including journals, number of articles published each year, and solution algorithms. We analyze recent literature on FJSP_PT, categorizing it based on algorithms into exact algorithms, heuristic algorithms, meta-heuristic algorithms, and swarm intelligence based algorithms. Finally, the research trends and challenges faced by FJSP_PT are summarized.
Key words: Flexible manufacturing system; Transportation vehicle; Processing machine; Integrated scheduling
1北京理工大学自动化学院,中国北京市,100081
2北京理工大学重庆创新中心,中国重庆市,401120
摘要:柔性制造系统中加工机器与转运车辆的联合调度问题已引起学术界和工业界的广泛关注。与传统柔性车间调度问题相比,将转运车辆调度纳入柔性制造系统的调度,使得联合调度问题的求解更加具有挑战性和实践意义。本文对联合调度问题的常见假设、约束、目标函数和基准算例作了归纳总结。然后,从出版期刊、历年发表文章数量以及求解方法等角度,对截至2023年的相关文献进行了统计和讨论。随后,根据解决方法的类型,将其分为精确算法、启发式算法、元启发式算法和群体智能算法,并梳理已有文献。最后,总结了联合调度问题的研究趋势和未来挑战。
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DOI:
10.1631/FITEE.2300795
CLC number:
TP273
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On-line Access:
2025-04-03
Received:
2023-11-22
Revision Accepted:
2024-02-20
Crosschecked:
2025-04-07