Salwani Abdullah

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Combinations of evolutionary based approaches with local search have provided very good results for a variety of scheduling problems. This paper describes the development of such an algorithm for university course timetabling. This problem is concerned with the assignment of lectures to specific timeslots and rooms. For a solution to be feasible, a number(More)
The university course timetabling problem consists, in essence, of assigning lectures to a specific timeslot and room. The goal is to satisfy as many soft constraints as possible while constructing a feasible schedule. In this paper, we present a variable neighbourhood search approach with an exponential monte carlo acceptance criteria. This heuristic(More)
Since the 1960’s, automated approaches to examination timetabling have been explored and a wide variety of approaches have been investigated and developed. In this paper we build upon a recently presented, sequential solution improvement technique which searches efficiently over a very large set of ‘adjacent’ (neighbourhood) solutions. This solution search(More)
The course timetabling problem deals with the assignment of a set of courses to specific timeslots and rooms within a working week subject to a variety of hard and soft constraints. Solutions which satisfy the hard constraints are called feasible. The goal is to satisfy as many of the soft constraints as possible whilst constructing a feasible schedule. In(More)
ABSTRACT University timetabling represents a difficult optimisation problem and finding a high quality timetable is a challenging task. With a large number of events involved and various hard constraints to be fulfilled, finding an optimal timetable is complicated and time consuming. Many approaches in the literature have addressed this problem. The(More)
Methodology for the Capacitated Examination Timetabling Problem Salwani Abdullah, Samad Ahmadi, Edmund K. Burke, Moshe Dror and Barry McCollum 1 Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science & Information Technology, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, United Kingdom.(More)
This work presents a tabu search and a memetic approach to an enrolment based course timetabling problem called Tabu-based memetic algorithm, the proposed approach employed crossover and mutation operators to a selected solution from the population. Then applying neighborhood structure randomly which is not in tabu-list to enhance the quality of the(More)
Since the 1960’s automated approaches to examination timetabling have been explored and a wide variety of approaches have been investigated and developed. In this paper we build upon a recently presented, sequential solution improvement technique which searches efficiently over a very large set of ‘adjacent’ (neighbourhood) solutions. This solution search(More)