应用改进遗传算法求解炼钢连铸生产调度问题

Appling an improved genetic algorithm for solving the production scheduling problem of steelmaking and continuous casting

  • 摘要: 炼钢连铸制造流程是一个复杂的多阶段、多产品生产过程,其生产调度问题可建模为车间调度问题.提出一个改进遗传算法求解炼钢连铸生产调度问题.改进包括三个方面:基于排序的适应度分配、基于排序的工件过滤交叉算子和基于指数关系的变异率曲线.经24个benchmark的比较测试表明,改进遗传算法比传统遗传算法的寻优能力更强.通过16个生产计划和6个处理工序的炼钢连铸生产调度实例计算结果表明,改进遗传算法是有效的.

     

    Abstract: The manufacturing flow of steelmaking and continuous casting is a complex multiple-phase and multiple-product production process.The production scheduling problem in this manufacturing flow can be seen as a job shop scheduling problem.An improved genetic algorithm for solving this problem was proposed and the improved aspects were as follows:rank-based fitness assignment,job filter order-based crossover operator,and mutation rate according to an exponential function relation.Twenty-four benchmarks were comparatively investigated and the result shows that the improved genetic algorithm has a better capacity of seeking optimum than a traditional genetic algorithm.The production scheduling problem of steelmaking and continuous casting with sixteen plans and six procedures was computed using the improved genetic algorithm.It is shown that the algorithm is effective.

     

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