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A greedy gradient-simulated annealing hyper-heuristic for a curriculum-based course timetabling problem.
- Source :
- 2012 12th UK Workshop on Computational Intelligence (UKCI); 1/ 1/2012, p1-8, 8p
- Publication Year :
- 2012
-
Abstract
- The course timetabling problem is a well known constraint optimization problem which has been of interest to researchers as well as practitioners. Due to the NP-hard nature of the problem, the traditional exact approaches might fail to find a solution even for a given instance. Hyper-heuristics which search the space of heuristics for high quality solutions are alternative methods that have been increasingly used in solving such problems. In this study, a curriculum based course timetabling problem at Yeditepe University is described. An improvement oriented heuristic selection strategy combined with a simulated annealing move acceptance as a hyper-heuristic utilizing a set of low level constraint oriented neighbourhood heuristics is investigated for solving this problem. The proposed hyper-heuristic was initially developed to handle a variety of problems in a particular domain with different properties considering the nature of the low level heuristics. On the other hand, a goal of hyper-heuristic development is to build methods which are general. Hence, the proposed hyper-heuristic is applied to six other problem domains and its performance is compared to different state-of-the-art hyper-heuristics to test its level of generality. The empirical results show that the proposed method is sufficiently general and powerful. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISBNs :
- 9781467343916
- Database :
- Complementary Index
- Journal :
- 2012 12th UK Workshop on Computational Intelligence (UKCI)
- Publication Type :
- Conference
- Accession number :
- 86492281
- Full Text :
- https://doi.org/10.1109/UKCI.2012.6335754