摘要
分布式车间作业计划与调度是一个典型的组合优化问题,而组合优化问题是遗传算法求解的领域。本文描述了分布式车间作业调度问题及其调度方法,结合分布式车间生产模式的实际情况,将模拟退火算法引入自适应遗传算法,提出了混合遗传算法(GASA);详细地阐述了分布式车间作业计划与调度问题的解决策略和操作过程,并以甘特图的方式给出了计算结果。与其它方法比较,混合遗传算法是解决分布式车间作业计划与调度问题的更为优良的方法。
In this paper , distribution method of planning and scheduling is analyzed, and the method is based on a hybrid genetic algorithm with simulated annealing. This paper studies how to use self- adapted genetic algorithm and hybrid genetic algorithm （GASA） to solve this problem and its application, and puts forward the computing result with pattern of GAMTT graph. In this paper, the author come to a conclusion that GASA is a more superior method to distribution job - shop problem than else.
出处
《长春理工大学学报（自然科学版）》
2005年第3期19-22,共4页
Journal of Changchun University of Science and Technology(Natural Science Edition)
基金
国防科技重点实验室基金项目(514580502-01-13003-02)
关键词
分布式车间作业调度
遗传算法
混合遗传算法
distribution method planning and scheduling
genetic algorithm
hybrid genetic algorithms
