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We consider a simplification of a typical university course timetabling problem involving three types of hard and three types of soft constraints. A MAX-MIN Ant System, which makes use of a separate local search routine, is proposed for tackling this problem. We devise an appropriate construction graph and pheromone matrix representation after considering(More)
In this paper we present an extension of ant colony optimization (ACO) to continuous domains. We show how ACO, which was initially developed to be a metaheuristic for combinatorial optimization, can be adapted to continuous optimization without any major conceptual change to its structure. We present the general idea, implementation, and results obtained.(More)
The university course timetabling problem is an optimisation problem in which a set of events has to be scheduled in timeslots and located in suitable rooms. Recently, a set of benchmark instances was introduced and used for an 'International Timetabling Competition' to which 24 algorithms were submitted by various research groups active in the field of(More)
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(More)
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract—In this paper, we introduce ACO MV , an ant colony optimization (ACO) algorithm that extends the ACO R algorithm for continuous optimization to tackle mixed-variable optimization problems.(More)
This paper presents an attempt to find a statistical model that predicts the hardness of the University Course Timetabling Problem by analyzing instance properties. The model may later be used for better understanding what makes a particular instance hard. It may also be used for tuning the algorithm actually solving that problem instance. The paper(More)
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