并行遗传算法在小学班级排课中的应用:粗粒度方法

2009 XXII International Symposium on Information, Communication and Automation Technologies Pub Date : 2009-12-04 DOI:10.1109/ICAT.2009.5348396

Nedim Srndic, Emir Pandzo, Mirza Dervisevic, S. Konjicija

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引用次数: 10

摘要

本文介绍了一种并行遗传算法在解决小学周课程表构建问题中的应用。时间表的构建是np完全和高度约束的问题，因此是一项计算密集型的任务。提出了一种并行遗传算法(PGA)，该算法具有特定的染色体表示和适应度评估方法，以及特定的重组和突变算子。建议的解决方案使用粗粒度PGA，它适合在Beowulf集群上执行。给出了实验结果，比较了同一算法的串行和并行执行时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The application of a Parallel Genetic Algorithm to timetabling of elementary school classes: A coarse grained approach

This paper describes the application of a parallel genetic algorithm that solves the weekly timetable construction problem for elementary schools. Timetable construction is NP-complete and highly constrained problem, and therefore represents a computationally intensive task. A Parallel Genetic Algorithm (PGA) is proposed with specific methods for chromosome representation and fitness evaluation, and specific recombination and mutation operators. The proposed solution uses a coarse grained PGA, which is suitable for execution on a Beowulf cluster. Experimental results are provided, with a comparison of serial and parallel execution times for the same algorithm.

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2009 XXII International Symposium on Information, Communication and Automation Technologies

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