约束传播+蚁群优化的自动化学校排课

2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2013-07-13 DOI:10.1109/IWCIA.2013.6624795

M. Koshino, Takahiro Otani

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引用次数: 0

摘要

本文提出了一种用于学校自动排课的混合蚁群算法——真正的全超前预测+蚁群优化(RFL+ACO)。在此之前，已经提出了一种基于约束传播的时间表调度算法——真正的全前向贪婪算法(real Full forward -ahead Greedy, RFLG)，并对一些实时时间表调度问题显示出良好的效果。该算法采用蚁群算法迭代学习待实例化变量的选择顺序和待赋值的选择策略。利用统一初中和高中的真实课程表数据进行了性能评价实验，结果表明所提出的算法可以构造出较好的课程表。

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Constraint propagation + Ant Colony Optimization for automated school timetabling

This paper shows a hybrid ant algorithm for automated school timetabling, Really Full Look-ahead + Ant Colony Optimization (RFL+ACO). Previously, a constraint propagation based timetabling algorithm, Really Full Look-ahead Greedy (RFLG), has been proposed and has shown good results for some real timetabling problems. We adopt Ant Colony Optimization (ACO) to this algorithm in order to iteratively learn a selection order of variables to be instantiated and a selection policy of values to be assigned. A performance evaluation experiment using a real timetable data of unified lower and upper secondary school has been conducted, and results show that the proposed algorithm can construct good timetables.

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2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)

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