基于混合优化算法的装配线平衡问题  

Assembly line balancing problem based on hybrid optimization algorithm

作　　者：方喜峰[1] 章振 张胜文[1] 王沾 于超 FANG Xifeng;ZHANG Zhen;ZHANG Shengwen;WANG Zhan;YU Chao(School of Mechanical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212000,China)

机构地区：[1]江苏科技大学机械工程学院,镇江212000

出　　处：《现代制造工程》2021年第4期20-25,32,共7页Modern Manufacturing Engineering

基　　金：国防基础科研基金项目(A0720133010);江苏省先进制造技术重点实验室开放基金资助项目(HGAMTL-1905);镇江市重点研发计划项目(GY2019003)。

摘　　要：为求解给定装配线生产节拍、最大化装配效率的装配线平衡问题,根据装配线的特点和平衡优化需求,分析了装配作业顺序、站位数量等因素对装配线站位内作业分配的影响,综合考虑装配线平衡率和平滑系数,建立了装配线平衡问题数学模型,并设计了一种结合遗传算法(Genetic Algorithm,GA)、蚁群算法(Ant Colony Optimization algorithm,ACO)的混合优化算法进行求解。采用遗传算法进行快速随机的全局搜索,并生成信息素矩阵初始分布,利用蚁群算法进行精确求解。最后通过标准案例测试,证明了该混合优化算法具有更高的优化效率,同时验证了算法的可行性和有效性。In order to solve the assembly line balance problem which maximize assembly efficiency for given assembly cycle time,based on the characteristics of the assembly line and balance optimization needs,the influence of the assembly operation sequence,number of stations and other factors on the process allocation within the assembly line station were analyzed,and a mathematical model of assembly line balance problem was constructed,which comprehensively considered the balance rate and smoothing coefficient of the assembly line.A hybrid optimization algorithm which combined Genetic Algorithm(GA)and Ant Colony Optimization algorithm(ACO)was designed to solve the problem.The genetic algorithm was used to perform a fast random global search and generate the initial distribution of pheromone,and the ant colony algorithm was used to accurately solve.Finally,the standard case test proves that the algorithm has higher optimization efficiency,and verifies the feasibility and effectiveness of the algorithm.

关 键 词：装配线 遗传算法 蚁群算法 平衡优化 

分 类 号：TH16[机械工程—机械制造及自动化]