A MAX-MIN Ant System for the University Course Timetabling Problem
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
A Tabu-Search Hyperheuristic for Timetabling and Rostering
Journal of Heuristics
Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization
Journal of Global Optimization
An Extended Implementation of the Great Deluge Algorithm for Course Timetabling
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Generating University Course Timetable Using Genetic Algorithms and Local Search
ICCIT '08 Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology - Volume 01
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Information Sciences: an International Journal
A hybrid fish swarm optimisation algorithm for solving examination timetabling problems
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
On the performance of Scatter Search for post-enrolment course timetabling problems
Journal of Combinatorial Optimization
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The university course timetabling problem involves assigning a given number of events into a limited number of timeslots and rooms under a given set of constraints; the objective is to satisfy the hard constraints (essential requirements) and minimize the violation of soft constraints (desirable requirements). In this study we employed a Dual-sequence Simulated Annealing (DSA) algorithm as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within DSA. The performance of our approach is tested over eleven benchmark datasets. Experimental results show that our approach is able to generate competitive results when compared with other state-of-the-art techniques.