Abstract:
In this research, we introduce a set of multi-neighbourhood strategies of iterated two-stage tabu search, ITMTS, to solve examination timetabling problems. This work is b...Show MoreMetadata
Abstract:
In this research, we introduce a set of multi-neighbourhood strategies of iterated two-stage tabu search, ITMTS, to solve examination timetabling problems. This work is based on the standard tabu search with some modifications that are derived from the neighbourhood structure. The neighbourhood structure has divided the neighbourhood search mechanism into two stages, vertical neighbourhood search and horizontal neighbourhood search. These search mechanisms will work alternately with different neighbourhood concentration and candidate evaluation. We test and evaluate ITMTS with the uncapacitated Carter benchmark datasets and standard Carter's proximity cost. Our results are comparable with other approaches that have been reported in the literature with regards to the Carter's benchmark dataset and have shown as a promising technique to be further enhanced.
Published in: 2009 2nd Conference on Data Mining and Optimization
Date of Conference: 27-28 October 2009
Date Added to IEEE Xplore: 01 December 2009
Print ISBN:978-1-4244-4944-6