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Optimizing scheduling problem using an estimation of distribution algorithm and genetic algorithm

机译:使用分布估计算法和遗传算法优化调度问题

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摘要

This paper presents a methodology for using heuristic search methods to optimize scheduling problem. Specifically, an Estimation of Distribution Algorithm (EDA) - Population Based Incremental Learning (PBIL), and Genetic Algorithm (GA) have been applied to finding effective arrangement of curriculum schedule of Universities. To our knowledge, ED As have been applied to fewer real world problems compared to GAs, and the goal of the present paper is to expand the application domain of this technique. The experimental results indicate a good applicability of PBIL to optimize scheduling problem.
机译:本文提出了一种使用启发式搜索方法优化调度问题的方法。具体而言,分配算法的估计(EDA)-基于人口的增量学习(PBIL)和遗传算法(GA)已用于发现大学课程表的有效安排。据我们所知,与GA相比,ED As已被应用于较少的现实世界中的问题,并且本文的目标是扩展该技术的应用范围。实验结果表明PBIL在优化调度问题上具有良好的适用性。

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