Study on Premature Convergence in Assembly Sequence Genetic Planning

Focusing on the problem of premature convergence existed in genetic algorithm for assembly sequence planning, the reasons were analyzed from genetic operations. It was pointed out that keeping population diversity and gene schema were the keys to avoid premature convergence. Checking up chromosomes and regulating them with the same mechanism alter genetic information or destroy schema structure. They also aggravate premature convergence. The influences of variation probability on population diversity and evolution progress were discussed in detail. To alleviate premature convergence, an extend operator was presented. It can enhance population diversity and local search ability by replacing the bad individuals with the son individuals produced by good individuals dithering. Supplantation operator was adopted to improve the evolution ability. It checks up difference between chromosomes of individuals and add a punish term to the little difference individual at initial evolutions. In order to prevent loss of available gene, gene repair strategy was presented to ill genes. Simulation results for an assembly sequence planning show validity of the presented algorithm