Hybrid integrated two-stage multi-neighbourhood tabu search-EMCQ technique for examination timetabling problem

In this research, we introduce a hybrid integrated two-stage multi-neighbourhood tabu search, ITMTS, with EMCQ method in solving an examination timetabling problem. Two search mechanisms of this method, vertical neighbourhood search and horizontal neighbourhood search, will work alternately in different stages with several neighbourhood options. This procedure is based on the enhanced ITMTS with stratified random sampling technique (to represent selected exams to be evaluated) where EMCQ technique is used in the horizontal neighbourhood stage as a diversification search mechanism. We test and evaluate this technique with the uncapacitated Carter's benchmark datasets by using the standard Carter's proximity cost. The results of this technique are comparable with other approaches that have been reported in the literature and have shown that this technique has a potential to be further enhanced.