多目标模拟退火算法求解混装线平衡与排序  

Multi-Objective Simulated Annealing Algorithm for Balancing and Sequencing of Mixed-Model Assembly Line

作　　者：姜东 唐秋华[1] 李梓响 吴玲 JIANG Dong;TANG Qiu-hua;LI Zi-xiang;WU Ling(College of Machinery and Automation,Wuhan University of Science and Technology,Hubei Wuhan 430081,China)

机构地区：[1]武汉科技大学机械自动化学院,湖北武汉430081

出　　处：《机械设计与制造》2018年第9期189-192,共4页Machinery Design & Manufacture

基　　金：国家自然科学基金资助项目(51275366;51305311)

摘　　要：针对混流装配线平衡排序优化问题,提出了一种多目标模拟退火算法。考虑到工位负载影响装配线的生产效率、工人越过工位边界干扰生产等问题,建立了以最小工位绝对负载偏差与最小工位越界距离的优化目标。所提出的模拟退火算法在初始化中将启发式任务分配规则融入平衡问题,根据产品投产需求随机生成产品序列;引入了基于帕累托阶层和拥挤距离作为多目标适应度评价指标;对帕累托前沿解集进行重启操作,避免算法陷入局部最优;采用一种新的接受策略,提高了算法寻优能力。通过测试标准问题实验,对所提出的算法进行参数校验。将所提出的算法与快速非支配遗传算法进行对比,采用收敛性和多样性两个评价指标,验证所提出算法的优越性。To solve the mixed-model assembly line balancing and sequencing,this study develops a multi-objective simulated annealing algorithm.Since the station workload affects the production efficiency of the assembly line and the situation of crossing the station boundary interferes production,two objectives are considered:minimizing absolute deviation of workloads and minimizing over-bound distance.The proposed multi-objective simulated annealing algorithm utilizes heuristic rule for assembly line balancing and a random product sequence according to the production requirements in the initialization process.The Pareto dominance and crowding distance are used as a multi-objective fitness evaluation index.Meanwhile,a restart mechanism of replacing the current solution with a solution from the Pareto frontier is applied to avoid the proposed algorithm being trapped into local optima.And a new acceptance strategy is adopted to improve searching capability.The parameter of MOSA is calibrated carefully by testing benchmark problems.Computational results demonstrate the superiority of the proposed algorithm by comparing it with the well-known non-dominated sorting genetic algorithm in convergence and diversity metric.

关 键 词：混流装配线 平衡排序优化 模拟退火算法 多目标优化 

分 类 号：TH16[机械工程—机械制造及自动化] F403.7[经济管理—产业经济]