关键词: U型装配线, 资源分配, 多目标优化, 快速非支配遗传算法

Abstract: To handle the production disruptions and workload fluctuations caused by equipment failure and order's change,the multiple parallel optional equipment in key process and assistant in production line were set up.For decision variables,the benders decomposition method was adopted to divide the origin problem into the main problem on allocating equipments and assistants and the sub-problems on assign tasks,which reduced the complexity of model solution;the Benders-based rapid Non-dominated Sorting Genetic Algorithm (BNSGA-Ⅱ) was put forward with three layers of coding and decoding to adapt to decision variables;the hierarchy structure and crowding distance of non-backtracing Pareto method were used to implement population evaluation and selection;the hierarchical genetic operator based on probability was proposed to widen the neighborhood structure,improve the optimization ability and avoid the local optimization.The proposed algorithm was analyzed by ratio of non-dominated solution,convergence of Pareto frontier solution and spread metric,and the result showed that the algorithm could obtain the approximate non-dominated solutions of Pareto optimal frontier and had good convergence and diversity by a comparison with MOGA and NSGA.

Key words: U-shaped assembly line, resources assignment, multi-objective optimization, fast elisit non-dominated sorting genetic algorithm