面向订单的混流装配线多目标调度研究  

Multi-objective scheduling of order-oriented mixed flow production line

作　　者：解占新[1] 闫玺铃 陆春月[2] XIE Zhan-xin;YAN Xi-ling;LU Chun-yue(Mechanical Department,Jinzhong University,Jinzhong 030619,China;College of Mechanical Engineering,North University of China,Taiyuan 030051,China)

机构地区：[1]晋中学院机械系,山西晋中030619 [2]中北大学机械工程学院,山西太原030051

出　　处：《机电工程》2021年第5期580-586,共7页Journal of Mechanical & Electrical Engineering

基　　金：山西省重点研发计划资助项目(20201603D121033)。

摘　　要：针对面向订单的混流装配线车间组装过程中出现堆叠的问题,对该类生产线特点进行了分析,提出了一种理论调度优化模型及其算法。建立了以车间交货时间的准时度和组件完工的同时度为目标函数的车间多目标调度优化模型;对粒子群算法进行了改进,设计了基于吸引子与自然选择的社会粒子群算法来求解多目标优化模型;研究了粒子群的信息描述方法,提出了兼有工序和工件信息的二维编码,将生产信息转化为编程语言,利用MATLAB进行了编程迭代计算和仿真,并对比分析了标准粒子群算法、社会粒子群算法、混合粒子群算法仿真的适应度值、最优解迭代次数,验证了所提算法的优越性。研究结果表明:该多目标调度优化模型在面向订单的混流装配调度问题方面具备有效性和合理性;所设计的社会粒子群算法寻优速度快,寻优效果好;调度方案机器最低利用率可达72.49%,很好地解决了装配的堆叠问题。Aiming at the stacking problem in the assembly process of the order-oriented mixed-flow assembly line workshop,the characteristics of this type of production line were analyzed,the theoretical scheduling optimization model and its algorithm were derived.A multi-objective scheduling optimization model was established with the punctuality of delivery time and the as objective functions of component completion simultaneity.The particle swarm optimization algorithm was improved and the social particle swarm optimization algorithm based on attractor and natural selection was designed to solve the multi-objective optimization model.The information description method of particle swarm was studied,and a two-dimensional coding method combining process and workpiece information were proposed.The production information was transformed into programming language,so that MATLAB could be used for programming iterative calculation and simulation.The fitness value and iteration times of optimal solution of standard particle swarm optimization,social particle swarm optimization and hybrid particle swarm optimization were compared and analyzed.The superiority of the proposed algorithm was verified.The results indicate that the model is effective and reasonable in the order-oriented mixed-flow assembly scheduling problem.The design of social particle swarm optimization algorithm is fast and effective.The minimum machine utilization rate of the scheduling scheme can reach 72.49%,which solves the assembly stacking problem.

关 键 词：面向订单 混流装配线 社会粒子群 二维编码 多目标优化 

分 类 号：TH165[机械工程—机械制造及自动化] TP18[自动化与计算机技术—控制理论与控制工程]