Several Strategies to Improve the Performance of Hyperheuristics for Academic Timetabling Design Problem

2010 IEEE Electronics, Robotics and Automotive Mechanics Conference Pub Date : 2010-09-28 DOI:10.1109/CERMA.2010.23

J. Soria-Alcaraz, Martín Carpio, H. Terashima-Marín, León Guanajuato

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引用次数: 2

Abstract

The Educational timetabling problem is a common and hard problem inside every educative institution, this problem tries to coordinate Students, Teachers, Classrooms and Timeslots under certain constrains that dependent in many cases the policies of each educational institution. The idea behind hyper-heuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. This paper presents several strategies to improve a GA-based method that produces general hyper heuristics for the educational timetabling design problem using API-Carpio methodology. The GA uses static-length representation, witch involves the complete encoding of a solution algorithm capable to solve schedule design instances. This hyper-heuristic is achieved by learning and testing phases using real instances from Leon Institute of Technology (LIT) producing encouraging results for most of the instances. Finally we analyze the quality of our hyper-heuristic in the context of real Academic Timetabling Design problem against past Investigations.

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提高学术课程表设计问题超启发式算法性能的几种策略

教育排课问题是每个教育机构内部普遍存在的难题，它试图在一定的约束条件下协调学生、教师、教室和时间，而这些约束条件在很多情况下取决于各个教育机构的政策。超启发式背后的思想是发现一些直接启发式的组合来解决各种各样的问题。本文提出了几种策略来改进基于遗传算法的方法，该方法使用API-Carpio方法为教育排课设计问题产生一般超启发式。该遗传算法采用静态长度表示，这涉及到能够求解调度设计实例的求解算法的完整编码。这种超启发式是通过使用来自Leon Institute of Technology (LIT)的真实实例的学习和测试阶段来实现的，对大多数实例产生了令人鼓舞的结果。最后，结合以往的调查，以实际的课程表设计问题为背景，分析了我们的超启发式算法的质量。

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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2010 IEEE Electronics, Robotics and Automotive Mechanics Conference

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