具有不同持续时间的健壮的COA计划

Luohao Tang, Cheng Zhu, Weiming Zhang, Zhong Liu
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引用次数: 6

摘要

COA(行动过程)计划包括资源分配和任务调度。传统上,解决这个问题的假设是任务持续时间是恒定的,目标是最小化完工时间。与此相反,本文假设任务持续时间可以在一个时间间隔内变化,目标是在给定截止日期的情况下最大化RM(鲁棒性度量),这对处理持续时间的不确定性是有意义的。提出了一种基于遗传算法(GA)和简单时态网络(STN)的COA规划方法,并通过实例说明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust COA planning with varying durations
COA (Course of Action) planning involves resource allocation and task scheduling. Traditionally, this problem is tackled with the assumption that task duration is constant and with the objective to minimize the makespan. In contrast to this, this paper assumes task duration can vary in a time interval and the objective is to maximize the RM (Robustness Measure) given the deadline, which makes sense to deal with the duration uncertainty. A COA planning method based on GA (Genetic Algorithm) and STN (Simple Temporal Network) is proposed and a COA planning instance is presented to illustrate the usefulness of this method.
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