关键词: 装配序列规划, 蚂蚁算法, 遗传算法, 混沌算法, 信息矩阵

Abstract: For the problem of general genetic algorithm in solving Assembly Sequence Planning (ASP) problem with slow search speed and massive repeated solutions,a new method for ASP was proposed in which ant colony algorithm,chaos algorithm and genetic algorithm were mixed,and the strategy of dynamic update population number was also introduced.The information matrix of evaluation index was established by using the information between the parts based on disassembly interference matrix.In earlier stage,ant colony algorithm was used for local search,and chaos-genetic algorithm was used for global search in the later stage.In the global search process,Logistic mapping was used to generate offspring of assembly sequence to avoid generating repeated solutions,and a certain proportion was set to select the searched solutions and update population number dynamically.To further improve the quality of discrimination sequence,a new evaluation index named coherence was introduced in which the application times of assembly tools and the changing times of assembly direction were combined,and aid tools were also introduced at the same time.The gear pump was taken as an example to compare with ant colony algorithm,genetic algorithm and chaos algorithm,and the proposed algorithm was more effective through analysis of the performance from aspects of fitness value,running time and convergence speed.

Key words: assembly sequence planning, ant colony algorithm, genetic algorithms, chaos algorithm, information matrix