Disassembly sequence planning method based on hybrid genetic particle swarm optimization algorithm

WANG Yu-xin, REN Shuai
（College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China）

Abstract: Aiming at the problem that the optimal solution can not be obtained efficiently or even can not be got through the existing disassembly sequence planning method, a kind of hierarchical disassembly priority diagram was designed, and hierarchical constraint matrix was used to ensure the priority constraints, then the method of random sequence compliance was established by studying the problem of disassembly sequence planning features and determining suitable encoding rules for disassembly sequence. The genetic algorithm crossover operator and mutation operator suitable for this problem were defined, and the genetic algorithm-particle swarm optimization which is suitable for disassembly sequence planning was proposed by combining the global search ability of genetic algorithm with the local search ability of particle swarm optimization. The results indicate that the optimal solution fitness, iteration times and running time of the algorithm are lower than those of previous algorithms, that is, the disassembly sequence with better fitness value can be obtained more efficiently, which shows its effectiveness and superiority.
Key words: hybrid optimization algorithm; disassembly sequence planning; global search; constraint optimization problem; hydraulic pump