Article2007

Evolution of Constraint Satisfaction Strategies in Examination Timetabling

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Scheduling and Timetabling Solutions Metaheuristic Optimization Algorithms Research Constraint Satisfaction and Optimization

Abstract

This paper describes an investigation of solving Examination Timetabling Problems (ETTPs) with Genetic Algorithms (GAs) using a non-direct chromosome representation based on evolving the configuration of Constraint Satisfaction methods. There are two aims. The first is to circumvent the problems posed by a direct chromosome representation for the ETTP that consists of an array of events in which each value represents the timeslot which the corresponding event is assigned to. The second is to show that the adaptation of particular features in both the instance of the problem to be solved and the strategies used to solve it provides encouraging results for real ETTPs. There is much scope for investigating such approaches further, not only for the ETTP, but also for other related scheduling problems.

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1996Examination Timetabling: Algorithmic Strategies and Applications 1994Fast practical evolutionary timetabling

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