关键词: 拆卸线平衡问题, 随机作业时间, 遗传算法, 局部邻域

Abstract: Aiming at the randomness characteristics of disassembly task time due to a lot of uncertain factors in the actual disassembly line,a stochastic model of disassembly line balancing problem was constructed which was based on the disassembly model for part precedence relation diagram definition and takes the number of workstations,the balance index and the stability index as the optimization objective under the premise of meeting the cycle time constraint,and an local neighborhood genetic algorithm based on Pareto was proposed.A decoding method for random operation time was designed.The global search of the population was realized by two kinds of crossover operations,and a local search strategy combining depth neighborhood and breadth neighborhood was constructed to expand the scope of local search and improve local search ability.The proposed algorithm was applied to solve two large-scale disassembly cases,and the result indicated the effectiveness of the proposed algorithm and the validity of the improvement strategy.By taking a television disassembly case including 27 tasks as an example,the practical application of the proposed model and algorithm was identified by analyzing the application process and result.

Key words: disassembly line balancing problem, stochastic task times, genetic algorithms, local neighborhood