MILP Models for Flexible Job Shop Scheduling with Spatial Constraints and Sequence Flexibility
Han, Yunjun(韩云君)1; Peng,Shaoming1,2; Shen, Zhen1; Tao,Zhikun1,2; Xiong, Gang1
2024
会议名称2024 IEEE 20th International Conference on Automation Science and Engineering
会议录名称2024 IEEE 20th International Conference on Automation Science and Engineering
页码6
会议日期2024年8月28
会议地点Bari,Italy
摘要

Within the evolving landscape of Industry 4.0, the significance of flexible job shop scheduling problems is on the rise. This study addresses a novel category of NP- hard scheduling problems: the flexible job shop scheduling problems that incorporate site routing and operation sequenc- ing flexibility. These problems are crucial and applicable in various contexts, including carrier-based aircraft scheduling, shipbuilding assembly scheduling, and cutting tool operation scheduling. For these problems, we present two new MILP models: Model-1 is a time-indexed model, and Model-2 is a precedence variable-based model. These models are evaluated under ten cases of the problems. Our findings indicate that the two models exhibit varying solution eiciencies when deal- ing with problems of diverse magnitudes. Model-2 performs better than Model-1 on small-scale problems, while Model-1 outperforms Model-2 on medium-scale problems.

收录类别EI
语种英语
七大方向——子方向分类决策智能理论与方法
国重实验室规划方向分类虚实融合与迁移学习
是否有论文关联数据集需要存交
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/57364
专题多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者Xiong, Gang
作者单位1.State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
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Han, Yunjun,Peng,Shaoming,Shen, Zhen,et al. MILP Models for Flexible Job Shop Scheduling with Spatial Constraints and Sequence Flexibility[C],2024:6.
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