Research in the field of examination timetabling has developed in two directions. The first looks at applying various methodologies to induce examination timetables. The second takes an indirect approach to the problem and examines the generation of heuristics or combinations of heuristics, i.e. hyper-heuristics, to be used in the construction of examination timetables. The study presented in t...

The general course timetabling problem consists of assigning courses to a specific timeslot and room. The goal is to satisfy as many soft constraints as possible while constructing a feasible schedule (i.e. one that satisfies all the hard constraints). In this paper, we present a composite neighbourhood structure with a randomised iterative improvement algorithm. Many relevant publications can ...

Two ant algorithms solving a simplified version of a typical university course timetabling problem are presented – Ant Colony System and MAX -MIN Ant System. The algorithms are tested over a set of instances from three classes of the problem. Results are compared with recent results obtained with several metaheuristics using the same local search routine (or neighborhood definition), and a refe...

Many complex timetabling problems have an underpinning bounded graph colouring component, a pattern penalisation component and a number of side constraints. The bounded graph colouring component corresponds to hard constraints such as “students are in at most one place at one time” and “there is a limited number of rooms” [1]. Despite the hardness of graph colouring, it is often easy to generat...

Although they are simple techniques from the early days of timetabling research, graph colouring heuristics are still attracting significant research interest in the timetabling research community. These heuristics involve simple ordering strategies to first select and colour those vertices that are most likely to cause trouble if deferred until later. Most of this work used a single heuristic ...

In this work, we propose a variant of the Honey-bee Mating Optimization Algorithm for solving educational timetabling problems. The honey-bee algorithm is a nature inspired algorithm which simulates the process of real honey-bees mating. The performance of the proposed algorithm is tested over two benchmark problems; exam (Carter’s un-capacitated datasets) and course (Socha datasets) timetablin...

We describe the design and implementation of a multi-objective course-timetabling system for the Science Division at Rollins College. In the traditional vertex-coloring approach to timetabling, all conflicts are regarded as equally undesirable, but when all such conflicts are considered, including those that might involve only one or two students, a conflict-free timetable is rarely attainable....

Here we introduce DePathos, a graphical tool for a timetabling constraint engine (Pathos). Since the core of Pathos is textbased and provides little user-interaction, finding an appropriate solution for large problems (1000-2000 variables) can be a very time consuming process requiring the constant supervision of a constraint programming expert. DePathos uses an incremental solution strategy. S...

A lot of research has been conducted on hyper-heuristics for examination timetabling. However, most of this work has been focused on an uncapacitated version of the problem. This study reports on evolving hyper-heuristics for a highly constrained version of the problem, namely, the set of problems from the second International Timetabling Competition (ITC ’07). Previous work has shown that usin...

Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied, soft constraints, however, may be violated, but should be satisfied as much as possible. This paper shows how to model our timetabling problem as a partial constraint satisfaction problem and ...