改进多目标模糊粒子群的经编机优化调度研究  

Research on Optimal Scheduling of Warp Knitting Machine Based on Improved Multi-Objective Fuzzy Particle Swarm

作　　者：潘子茜 郗欣甫 李硕 季诚昌[1] PAN Ziqian;CHI Xinfu;LI Shuo;JI Chengchang(College of Mechanical Engineering,Donghua University,Shanghai 201620,China)

机构地区：[1]东华大学机械工程学院,上海201620

出　　处：《机械设计与制造》2024年第12期368-373,共6页Machinery Design & Manufacture

基　　金：国家重点研发计划资助(2018YFB1308800)。

摘　　要：经编车间的生产调度存在大规模、非线性、强耦合等复杂特性,属于NP-Hard(Non-Deterministic Polynomial Hard)问题。将其类化为无关并行机问题(Unrelated Parallel Machine Scheduling Problem,UPMSP),以最小化最大完成时间(Makespan)和最小提前/延迟惩罚成本为优化目标,提出一种改进的多目标模糊粒子群算法(f-MOPSO)。依据经编车间的实际订单情况,针对性设计了粒子的编码和解码,并且对算法的初始化、粒子飞行的惯性权重、粒子群多样性三个方面进行优化。通过工厂实测数据进行分析,证明了其在经编车间调度问题上的有效性,解决了实际生产中的降本增效需求。The production scheduling of warp knitting workshop has complex characteristics such as large-scale,non-linearity,and strong coupling,which is a Non-Deterministic Polynomial Hard Problem.The classifies it as an Unrelated Parallel Machine Problem,and takes minimizing the maximum completion time and the minimum advance/delay penalty cost as the optimization goals,and proposes an improved multi-objective fuzzy particle swarm algorithm.According to the actual order situation of the warp knitting workshop,the coding and decoding of the particles are designed specifically,and the initialization of the algorithm,the inertial weight of the particle flight,and the diversity of the particle swarm are optimized.The test proved its effectiveness in the warp knitting workshop scheduling problem,and solved the demand for cost reduction and efficiency increase in actual production.

关 键 词：经编车间 调度优化 模糊粒子群 多目标 无关并行机 

分 类 号：TH16[机械工程—机械制造及自动化] TH186