An Improved Genetic Algorithm with Local Search for Solving the DJSSP with New Dynamic Events

K. Ali, A. Telmoudi, Said Gattoufi
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引用次数: 5

Abstract

This paper addresses an improved Genetic Algorithm (GA) combined with local search technique to solve the dynamic job shop scheduling problem (DJSSP) with new job arrivals and change in processing time. The objective function is the minimization of the makespan known to be one of the performance criterion used to optimize manufacturing system requirements. To enhance the scheduling process, a rescheduling strategy is used to solve dynamic disturbances. Various problems including the number of jobs, the number of machines and the number of new job arrivals are compared with a collection of state of the art Dispatching Rules(DRs) and other metrics. Obtained results are satisfactory for rescheduling of new job arrivals, change in processing time and makespan minimization.
一种改进的局部搜索遗传算法求解带有新动态事件的DJSSP
本文提出了一种结合局部搜索技术的改进遗传算法,用于解决具有新作业到达和加工时间变化的动态作业车间调度问题。目标函数是最大完工时间的最小化,这是用于优化制造系统需求的性能标准之一。为了提高调度效率,采用重调度策略来解决动态干扰。各种各样的问题,包括工作的数量,机器的数量和新工作到达的数量,与最先进的调度规则(dr)和其他指标的集合进行比较。所得结果对于新作业的重新调度、加工时间的改变和最大完工时间的最小化都是令人满意的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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