模糊遗传算法在机器调动问题运用

单机器调度问题是研究工件在多道工序进行加工的加工活动排序的组合最优化问题.由于调度问题中绝大多数属于NP难类问题,不存在有效的最优求解算法.针对用智能优化算法-遗传算法求解单机器调度问题中交叉率和变异率难以确定的问题,设计了一种模糊算法以便自动确定交叉率和变异率.通过数值实验,嵌入模糊规则的遗传算法比简单的遗传算法要好,说明在实际生产中,此算法具有强大的发展前途.

Hybrid Genetic Algorithms with Fuzzy Logic Controller

New implementation of genetic algorithms (GAs) is developed for machine scheduling prob- lem. Machine scheduling problem is abundant among modern manufacturing system. The performance mea- sure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simu- ltaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we proposed a hybrid genetic algorithms approach is deal with in order to adjust the crossover probability and mutation probability by fuzzy logic controller whereas the hybrid genetic algorithm does not require prelimi- nary experiments to determine probabilities for genetic operators. The experimental results show the effecti- veness of the proposed GAs method.