求解柔性作业调度的共生进化算法

Improved Evolutionary Algorithm for Job Flexibility Schedule

在柔性作业处理系统中,运行操作的机器、操作运行顺序及完成特定加工的操作集等均可含有柔性,作业调度的最优性依赖流程设计的结果。该文在共生遗传算法求解此问题的基础上,定义了一种新的适应度函数,将个体所参与的所有组合解的算术平均值作为此个体的适应度。引进较优的遗传交叉方法。仿真结果证明,新的适应度函数表现优异,对给定的复杂调度问题得到了更好的解。

Process planning and job-shop schedule are closely related with each other in flexible manufacturing system. The optimality of job-shop scheduling depends on the result of process planning. Symbiotic evolutionary algorithm is used to deal with this problem usually. This paper presents a new definition of individual＇s fitness to improve the performance of the algorithm. Simulation results demonstrate the effectiveness of the proposed definition, whose optimization performance is markedly superior to those in the literature and can get much better solutions and cost less time. A new genetic operation is also introduced. Experimental results also indicate the method efficiently improves the performance of the symbiotic evolutionary algorithm.