The Examination Timetabling problem regards the scheduling for the exams of a set of university courses, avoiding the overlapping of exams having students in common, fairly spreading the exams for the students, and satisfying room capacity constraints. We present a family of solution algorithms for a set of variants of the Examination Timetabling problem. The algorithms are based on tabu search...

This paper presents our work on analysing high level heuristics within a graph based hyper-heuristic framework. Local search based methods (Tabu Search and steepest descent method) are compared as the high level heuristics within the graph based hyper-heuristic framework and the analysis of their neighborhood structures and performance on the high level landscape is carried out. An iterated ste...

University timetabling problems are a yearly challenging task and faced repeatedly each semester. The considered non-polynomial time (NP) combinatorial optimization (COP), which means that they can be solved through algorithms to produce the aspired optimal timetable. Several techniques have been used solve university problems, most of them use techniques. This paper provides comprehensive revi...

Although there has been a fair amount of research in the area of school timetabling, this domain has not developed as well as other fields of educational timetabling such as university course and examination timetabling. This can possibly be attributed to the fact that the studies in this domain have generally been conducted in isolation of each other and have addressed different school timetab...

The research presented in this PhD thesis contributes to a larger project to develop a case-based reasoning (CBR) meta-heuristic selector for examination timetabling problems. Chapter 2 gives a detailed survey of techniques in the literature applied to examination timetabling. The work in this thesis aims to provide a significant contribution to the examination timetabling domain in its own rig...

The university course timetabling is known to be a highly constrained optimization problem, more complex than examination timetabling. Many different approaches, including evolutionary algorithms, tabu search, simulated annealing, and their hybrids, are developed for solving the problem. The negative selection algorithm, an algorithm inspired by the immune system, has successfully been applied ...