摘要
车间调度问题计算复杂,约束条件度,一般算法难以实现全局搜索,算法比较容易陷入局部最优。通过对柔性车间调度问题的深入研究,采用遗传算法进行柔性车间调度,使一个个体可以表达全部零件加工顺序,并用适应度函数平价个体好坏。种群通过选择算子、交叉算子和变异算子不断进化,最终得到最优的柔性车间调度方法。通过仿真试验表明,该算法能够有效地进行车间调度。
Due to the computational complexity and restrictive conditions in job-shop scheduling,common arithmetic often falling into local optimum.Through further study in flexible job-shop scheduling,GA is used to solve the problem.Each individual is encoded to represent the whole processing order.Fitness function is used to evaluate each individual.Swarm get best flexible job-shop scheduling plan thought selection,cross and mutation operation.The emulation experiment shows that GA can carry on flexible job-shop scheduling effectively.
出处
《电脑知识与技术》
2010年第8X期6837-6839,共3页
Computer Knowledge and Technology
关键词
车间调度
柔性
遗传算法
模糊目标
job-shop scheduling
flexible
genetic algorithms
fuzzy goal
