A hybrid fish swarm optimisation algorithm for solving examination timetabling problems

Authors:
Hamza Turabieh;Salwani Abdullah
Affiliations:
Computer Science Department, Faculty of Science and Information Technology, Zarka University, Jordan;Data Mining and Optimisation Research Group (DMO), Center for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
Venue:
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Year:
2011

Citing 11
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Abstract

A hybrid fish swarm algorithm has been proposed to solve exam timetabling problems where the movement of the fish is simulated when searching for food inside water (refer as a search space). The search space is categorised into three categories which are crowded, not crowded and empty areas. The movement of fish (where the fish represents the solution) is determined based on a Nelder-Mead simplex search algorithm. The quality of the solution is enhanced using a great deluge algorithm or a steepest descent algorithm. The proposed hybrid approach is tested on a set of benchmark examination timetabling problems in comparison with a set of state-of-the-art methods from the literature. The experimental results show that the proposed hybrid approach is able to produce promising results for the test problem.