用遗传算法求解可变机器约束的Job-shop调度问题

A Genetic Algorithm for Job-shop Scheduling Problem with Alternative Machine

  • 摘要: 描述了可变机器约束的Job-shop调度问题模型,并提出了一种基于遗传算法的调度算法进行求解.采用了一种新的基于操作的染色体编码方式,用二维矩阵的形式在机器的表达形式上扩展了传统基于操作的编码方式.在进化过程中设计了一种改变算子附加信息方法的操作,用于扩展种群的变化方式和算法的搜索范围.最后,分别以满足交货期和总加工时间最小为调度目标进行了数值计算,表明了该方法的有效性.

     

    Abstract: Job-shop scheduling problem model with alternative machines is described. Based on genetic algorithms, a scheduling approach is presented, which can be used to solve the problem. A new chromosome representation with two-dimensional matrix is designed, which can enlarge traditional coding mode based on operators in expression of the machines. A new operation is introduced to change the extra information of the operator during the evolution process. The effectiveness of the proposed algorithm is verified by computation results (digital experiments) with two different scheduling objectives.

     

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