【摘要】 为了对装配环境下的车间作业进行调度,提出了一种基于可行域搜索的遗传算法。为保证算法在进化过程中染色体始终保持合法性和可行性,在种群的初始化、交叉和变异等阶段,分别设计实现了首代修复算子、可行域交叉算子和可行域变异算子。可行域交叉算子和可行域变异算子的设计组合实现了算法的可行域搜索,减小了搜索空间,省去了复杂的解码修复操作,提高了求解效率,为解决复杂的装配车间调度问题提供了有价值的参考。通过与简单规则、禁忌搜索、普通遗传算法实验结果的比较,验证了所提算法的合理性和优越性。更多还原

【Abstract】 To solve the Job Shop scheduling problems in assembly environment,a genetic algorithm based on feasible solution space searching named Feasible Solution Space Genetic Algorithm(FSSGA) was proposed.To ensure the validity and feasibility of chromosomes in the whole evolution process,the first generation of repair operator in the stage of population initialization,the feasible crossover operator in the stage of crossover and the feasible mutation operator in the stage of mutation were designed and realized.The combinatorial design of feasible crossover operator and feasible mutation operator realized the feasible solution search of FSSGA,which not only reduced the searching space but also omitted the complex operations of decoding and repairing.FSSGA improved the solution efficiency and provided valuable reference for solving complex assembly Job Shop scheduling problems.The rationality and superiority of FSSGA was embodied in the comparative experiment of simple rules,tabu search,simple genetic algorithm and FSSGA.更多还原