文章基本信息

标题：Comparing Performance of Genetic Algorithm with Varying Crossover in Solving Examination Timetabling Problem
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作者：Omar Ibrahim Obaid ; MohdSharifuddin Ahmad ; Salama A. Mostafa 等
期刊名称：Journal of Emerging Trends in Computing and Information Sciences
电子版ISSN：2079-8407
出版年度：2012
卷号：3
期号：10
页码：1427-1434
出版社：ARPN Publishers
摘要：In this paper, a genetic-based approach to examination timetable scheduling problem is presented. In particular, the variations that are observed in the Genetic Algorithm (GA) performance in generating possible timetables are studied. A timetable with binary representation is applied with several operators with the aim of preventing the violation of the fundamental constraints. The algorithm is guaranteed to always produce a feasible solution by satisfying the hard constraints. It utilizes one-point and two-point crossover operators and propagates distinctive timetable features to generate better solutions even for complex cases. However, different operators and their impact on the quality of the timetables are also demonstrated. It is found that GA influence can be affected by adjustment to its parameters.
关键词：Examination timetabling; hard and soft constraints; genetic algorithm