基于遗传算法的作业车间调度优化求解方法

针对 job shop调度问题 ,提出了一种遗传算法编码方法和解码方法。该方法根据问题的特点 ,采用一种按工序用不同编号进行的染色体编码方案 ,并采用矩阵解码方法。此编码与调度方案一一对应 ,并且该编码方案有多种交叉操作算子可用 ,无须专门设计算子。算例计算结果表明 ,该算法是有效的 ,适用于解决 job shop调度问题 ,通过比较 ,该遗传算法优化 job shop调度操作简单并且收敛速度快。

Method for GA-based solution to job shop scheduling optimization

This paper proposed a new encoding method and decoding method with the matrix form for a solution to genetic algorithm-based job shop scheduling problem.Based on a specific problem,designed a job activities' number-dependent coding of chromosomes and adopted the matrix decoding.As a result,codes by the new encoding method accord with the job scheduling schemed one-to-one were able to match multiple cross operators without a special design of operators.Result from a case study show that the genetic algorithm with the help of new encoding method presented a powerful ability and was able to effectively solve job shop scheduling problems.To show merits of the new encoding and decoding method,a comparison of different sized job shop scheduling problems in terms of job activity duration,sequence,and scheduling schemes,showed that with the help of the proposed method the genetic algorithm is encouraging,with solutions found through simple operations and fast convergence.