We present here a metaheuristic approach to the university course timetabling problem using a memetic algorithm with a very effective local search. The algorithm was tested on the International Timetabling Competition benchmark instances. Results are encouraging and show that evolutionary computation with the help of local search can compete with succesful algorithms on the problem.

Yongkai Liu, Defu Zhang and Francis Y.L. Chin Department of Computer Science, Xiamen University, Xiamen 361005, China Department of Computer Science, University of Hong Kong, Hong Kong Abstract Constructing a feasible solution, where the focus is on “hard” constraints only, is an important part of solving timetabling problems. For the University Course Timetabling Problem (UCTP), we propose a h...

We consider an academic timetabling and rostering problem involving periodic retraining of large numbers of employees at an Australian electricity distributor. This problem is different from traditional high-school and university timetabling problems studied in the literature in several aspects. We propose a three-stage heuristic consisting of timetable generation, timetable improvement, and tr...

This paper describes the application of a hybrid genetic algorithm to a real-world instance of the university course timetabling problem. We address the timetabling of laboratory exercises in a highly constrained environment, for which a formal definition is given. Solution representation technique appropriate to the problem is defined, along with associated genetic operators and a local search...

In this paper we have presented a combination of two metaheuristics, namely great deluge and tabu search, for solving the university course timetabling problem. This problem occurs during the assignment of a set of courses to specific timeslots and rooms within a working week and subject to a variety of hard and soft constraints. Essentially a set of hard constraints must be satisfied in order ...

Many complex timetabling problems, such as university course timetabling [1, 2] and employee rostering [3], 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 “each student attends all events of courses of his choice, no student can be in two room...

This is to certify that we have read this thesis and that we find it fully adequate in scope, quality and content, as a thesis for the degree of Master of Science. continously asking me " how is the thesis going? " , because she encouraged me to persevere without knowing it. Also I would like to thank to my best friend, my colleague, my dear husband Tarkan Aydın for his understanding, patience,...

This work presents a Particle Collision Algorithm (PCA) to solve university course timetabling problems. The aim is to produce an effective algorithm for assigning a set of courses, lecturers and students to a specific number of rooms and timeslots, subject to a set of constraints. PCA approach that was originally introduced by Sacco for policy optimization. PCA always accepts improved solution...

Habibollah Haron Department of Computer Science, Faculty of Computing (FC), UniversitiTeknologi Malaysia, Malaysia Emai: [email protected] Abstract: The course timetabling problem is not a trivial task as it is an NP-hard and NP-complete problem and many solutions have been proposed due to its high complexity search landscape. In essence, the nature of the course timetabling problem is to assign a l...

There has been a growing desire for methodological support for the development of knowledge based systems, and the KADS methodology is probably the most widely known methodology in Europe. However, KADS has been criticised for the overhead which it places on small and medium-sized KBS projects where the risks of KBS development becoming unmanageable are relatively low. This paper describes the ...