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集成式工艺规划与车间调度问题研究现状及发展 被引量:4

Current research and progress on integrated process planning and scheduling problem
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摘要 集成式工艺规划与车间调度(IPPS)问题的研究对于制造系统整体性能的提高具有重要意义,综述与分析了近年来IPPS问题研究的发展现状。概述了IPPS的3种主要建模方法,分析了特定生产环境下工艺规划与车间调度进行集成的特殊性。从单目标优化与多目标优化两方面综述了IPPS求解方法的研究概况,分析了多目标IPPS求解方法研究中存在的问题。总结了不确定扰动下的IPPS问题及面向绿色制造的IPPS问题研究现状,分析了2种情况下IPPS模型构建和求解方法设计上带来的新问题。基于上述综述分析,展望了未来开展集成式工艺规划与车间调度问题研究的一些方向。 The research of integrated process planning and scheduling(IPPS)is of great significance in the improvement of the overall performance of the manufacturing system.This paper reviews and analyzes the development status of IPPS.The three main modeling methods of IPPS are summarized,and the particularity of the integration of process planning and scheduling in a specific production environment is analyzed.The overview of research on IPPS solution method is summarized from two aspects:single-objective optimization and multi-objective optimization,and the problems in the research of multi-objective IPPS solution method are analyzed.In addition,the research status of the IPPS problem under uncertain disturbances and the IPPS problem for green manufacturing are summarized,and the new problems caused by the IPPS model construction and solution method design in the two cases are analyzed.Based on the above summary and analysis,some directions for future research on IPPS are prospected.
作者 文笑雨 王康红 孙海强 高亮 WEN Xiaoyu;WANG Kanghong;SUN Haiqiang;GAO Liang(Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,Zhengzhou 450002,P.R.China;School of Mechanical and Electrical Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,P.R.China;State Key Laboratory of Digital Manufacturing Equipment&Technology,Huazhong University of Science and Technology,Wuhan 430074,P.R.China)
出处 《重庆大学学报》 EI CAS CSCD 北大核心 2021年第2期120-128,共9页 Journal of Chongqing University
基金 国家自然科学基金资助项目(51905494,51805330) 教育部人文社会科学研究青年基金资助项目(19YJCZH185) 河南省科技攻关项目(202102210088)。
关键词 集成式工艺规划与车间调度 绿色制造 多目标优化 integrated process planning and scheduling green manufacturing multi-objective optimization
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