关键词: 作业车间, 多机器人, 制造单元, 调度, 析取图, 遗传算法, 邻域搜索

Abstract: Based on the characteristics of job-shop robotic manufacturing cell scheduling problem,an improved genetic algorithm by integrating heuristic rules and neighborhood search strategy was researched,which was aimed at minimizing the maximum completion time.A mathematical optimization model and an improved disjunctive graph model for job-shop robotic manufacturing cell scheduling problem were established.Based on key path of disjunctive graph model,the moving machine block,changing robot block and adjusting robot task allocation were used to construct the search neighborhood,and the three layer scheduling method by integrating procedure insertion method and task allocation method of heuristic moving were used to initialize the population.Neighborhood structures-based local search algorithm was combined with three layer scheduling-based genetic algorithm to solve the problem effectively.Benchmark tests showed that the improved genetic algorithm was effective and was superior to other algorithms.

Key words: job-shop, multi-robots, manufacturing cell, scheduling, disjunctive graph, genetic algorithms, neighborhood search