求解多Hoist循环调度问题的帝国主义竞争算法  

Multi-Hoist Cyclic Scheduling Based on Imperialist Competitive Algorithm

作　　者：毛永年 唐秋华 张利平 MAO Yong-nian;TANG Qiu-hua;ZHANG Li-ping(College of Engineering and Technology,Zunyi Normal University,Guizhou Zunyi563000,China;Key Laboratory of Metallurgical Equipment and Control Technology,Wuhan University of Science and Technology,Hubei Wuhan430081,China;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering,Hubei Wuhan University of Science and Technology,Hubei Wuhan430081,China)

机构地区：[1]遵义师范学院工学院,贵州遵义563000 [2]武汉科技大学冶金装备及其控制教育部重点实验室,湖北武汉430081 [3]武汉科技大学机械传动与制造工程湖北省重点实验室,湖北武汉430081

出　　处：《机械设计与制造》2020年第5期54-58,共5页Machinery Design & Manufacture

基　　金：中国博士后科学基金资助项目(2013M542073)。

摘　　要：自动化的电镀生产线通常设计有多台受计算机控制的Hoist(物料搬运设备),以便生产大批具有柔性制造特征的产品。基于搬运作业的最小时间间隔法,构建了多Hoist循环调度问题的混合整数线性规划模型,并首次使用基于群智能的元启发式算法(帝国主义竞争算法)求解该问题。借鉴遗传算法的进化机制,分别对搬运作业的优先关系序列、Hoist的分配序列进行不同的交叉、变异操作以实现帝国主义竞争算法的同化过程。针对种群进化过程中产生的大量不可行解,提出基于Hoist分配的不可行解修复策略以修复搬运作业优先关系。最后,基于标杆案例和随机案例,分别与专业优化软件CPLEX以及遗传算法进行对比,测试结果验证了所提出的方法的有效性。Automated electroplating production lines are usually designed with multiple hoists which are controlled by computer,so as to produce a large number of products with flexible manufacturing characteristics. Based on the method of minimum time interval between handling tasks,a mixed integer linear programming model for multi-hoist cyclic scheduling is constructed.And for the first time,a meta-heuristic algorithm based on swarm intelligence(imperialist competitive algorithm,ICA)is utilized to solve this problem. Assimilation stage of ICAis performedby implementing different crossover and mutation operations on priority sequence of handling tasksand hoist sequence,which is brought fromgenetic algorithm(GA).A repair strategy is proposed to repair unfeasible priority relationship. At last,based on benchmark and randomly generated instance,the effectiveness of the proposed method is demonstrated by comparing the results of CPLEX and GA.

关 键 词：帝国主义竞争算法 多Hoist循环调度 柔性制造 修复策略 

分 类 号：TH16[机械工程—机械制造及自动化] F224[经济管理—国民经济]