首页> 外文会议>International Conference on Evolutionary Multi-Criterion Optimization(EMO 2005); 20050309-11; Guanajuato(MX) >Proposition of Selection Operation in a Genetic Algorithm for a Job Shop Rescheduling Problem
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Proposition of Selection Operation in a Genetic Algorithm for a Job Shop Rescheduling Problem

机译:求解车间调度问题的遗传算法中的选择运算命题

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摘要

This paper deals with a two-objective rescheduling problem in a job shop for alteration of due date. One objective of this problem is to minimize the total tardiness, and the other is to minimize the difference of schedule. A genetic algorithm is proposed, and a new selection operation is particularly introduced to obtain the Pareto optimal solutions in the problem. At every generation in the proposed method, two solutions are picked up as the parents. While one of them is picked up from the population, the other is picked up from the archive solution set. Then, two solutions are selected from these parents and four children generated by means of the crossover and the mutation operation. The candidates selected are not only solutions close to the Pareto-optimal front but also solutions with a smaller value of the total tardiness, because the initial solutions are around the solution in which the total tardiness is zero. For this purpose, the solution space is ranked on the basis of the archive solutions. It is confirmed from the computational result that the proposed method outperforms other methods.
机译:本文讨论了在车间更改到期日的两目标重新计划问题。这个问题的一个目的是使总拖延最小化,另一个目的是使时间表之间的差异最小化。提出了一种遗传算法,并特别引入了一种新的选择运算来获得问题中的帕累托最优解。在提出的方法的每一代中,都有两个解决方案作为父级。尽管其中一个是从总体中选取的,而另一个是从存档解决方案集中选取的。然后,通过交叉和变异操作从这些父母和四个孩子中选择两个解决方案。选择的候选对象不仅是接近帕累托最优前沿的解,而且​​是总拖尾值较小的解决方案,因为初始解决方案围绕总拖尾率为零的解决方案。为此,将根据归档解决方案对解决方案空间进行排名。从计算结果可以看出,该方法优于其他方法。

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