文章基本信息

标题：Hybridizing Genetic Algorithm and Record-to-Record Travel Algorithm for Solving Uncapacitated Examination Timetabling Problem
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作者：Munther Hameed Abed ; Alicia Y.C. Tang
期刊名称：electronic Journal of Computer Science and Information Technology
出版年度：2013
卷号：4
期号：1
语种：English
出版社：College of Information Technology, Universiti Tenaga Nasional
摘要：Examination timetabling is one of the most important administrative tasks in academic institutions. They are used to schedule examinations into timeslots and rooms. Many methods have been developed to solve examination timetabling problems. Metaheuristics have shown good results especially if they are hybridized with other methods. Genetic Algorithms (GAs) are one of the techniques that have been used in optimization problems. Record-to-Record Travel (RRT) is another optimization method that has been introduced for local search. In this paper, we describe the combined use of GA and RRT, called GARRT. In particular, the process of hybridization of the two algorithms to solve the uncapacitated examination timetabling problems is discussed. GARRT aims to balance the global search (by GA) and the local search (by RRT). This work uses Carter’s benchmark datasets as the testbed. Simulation results showed that GARRT performed better when compared to the results generated by GA approach alone. A good result is achieved by minimizing the violation of the soft constraints.