具有不同到期日和放行时间的单机调度的混合遗传方法

Jae-Gyun Kim
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引用次数: 6

摘要

本文研究了具有不同发布时间和到期日的n作业、非抢占和单机调度问题,即最小化早、迟和的总和。为了解决这一问题,提出了一种混合遗传算法,并引入了新的交叉和变异算子来调整作业排序。为了研究参数集的适宜性和解的质量,本文评价了用枚举法求解小规模问题时对应解的个数和收敛到最优解的速度。为了证明所提出的遗传算法的性能,通过求解大量问题对其进行了经验评估,并与使用现有算子的遗传算法得到的解进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hybrid genetic approach for single machine scheduling with distinct due dates and release times
The article addresses the n-job, non-preemptive and single machine scheduling problem of minimizing the sum of earliness and tardiness with different release times and due dates. To solve the problem, it proposes a hybrid genetic algorithm with a new crossover and mutation operators to adjust the job sequencing. To investigate the suitability of the parameters set and the quality of the solution, the article evaluates the number of corresponding solutions and the speed of converging to an optimal solution which is solved by an enumeration method for small size problems. To demonstrate the performance of the proposed GA, it is empirically evaluated by solving a large number of problems and compared with solutions obtained by genetic algorithms using the existing operators.
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