一种求解柔性作业车间调度问题的混合智能算法  

Research on Multi-objective Flexible Job-shop Scheduling Problem Based on Hybrid Intelligence Algorithm

作　　者：武福[1,2] 张治娟[2] 

机构地区：[1]甘肃省轨道交通装备系统动力学与可靠性重点实验室,兰州730070 [2]兰州交通大学机电工程学院,兰州730070

出　　处：《组合机床与自动化加工技术》2013年第5期130-133,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：甘肃省自然科学基金(1112RJZA045)

摘　　要：提出了一种将蚁群算法、遗传算法和粒子群算法优化融合的混合智能算法,并将其应用于解决多目标柔性作业车间调度问题。采用蚁群算法寻径生成初始群体,利用遗传算法进行调度路径的优化,利用粒子群算法对蚁群算法中的信息素进行优化,优势互补。最后通过仿真实例验证了该算法的可行性和有效性。This paper proposed a hybrid intelligence algorithm to solve multi-objective flexible job-shop scheduling that was based on the combination of ant colony algorithm, genetic algorithm and particle swarm optimization. First, it adopted ant colony algorithm to get a new population by routing. Second it made use of genetic algorithm to optimize the path, the PSO algorithm to optimize the pheromone in ant colony algorithm. Finally, it developed enough advantage of the three algorithms. The simulation results show that the algorithm is feasible and effective.

关 键 词：蚁群算法 多目标优化 柔性作业车间调度 

分 类 号：TH165[机械工程—机械制造及自动化] TG65[金属学及工艺—金属切削加工及机床]