关键词: 拆卸线平衡, 多目标优化, 遗传算法, 模拟退火算法, Pareto解集

Abstract: Aiming at the deficiencies of single solving result and failure to balance the optimization objectives of traditional method in solving multi-objective disassembly line balancing problem,a multi-objective genetic simulated annealing algorithm based on Pareto set was proposed,which combined rapid global search ability of genetic algorithm with strong local search capability of simulated annealing operation.The simulated annealing operation was performed on the solving results of genetic operation to avoid the local optimum.An improved Metropolis rule was employed by considering the characteristics of multi-objective optimization problems.The crowding distance as an evaluation mechanism was adopted to filter the non-inferior solutions acquired from Pareto dominance relationship,and the preserved non-inferior solutions were added in the population to speed up the convergence rate of the proposed algorithm.Based on a 25-task disassembly case,the effectiveness of proposed algorithm was verified by the comparison with other 6 single-objective algorithms.The proposed algorithm was applied to a disassembly instance and 10 task assignment schemes were obtained,and the solution results were compared with Pareto ant colony algorithm further indicating the superiority of proposed algorithm.

Key words: disassembly line balancing, multi-objective optimization, genetic algorithms, simulated annealing algorithm, Pareto set