The application of a Parallel Genetic Algorithm to timetabling of elementary school classes: A coarse grained approach

Šrndić, Nedim; Pandzo, Emir; Dervisevic, Mirza; Konjicija, Samim

doi:10.1109/icat.2009.5348396

Cited by 3 publications

(1 citation statement)

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“…Abramson et al [1] and Srdnic et al [11] employ a parallel genetic algorithm to solve artificial school timetabling problems. Caldierra et al [5] also apply GAs to solve a generated school timetabling problem.…”

Section: Introductionmentioning

confidence: 99%

The effect of construction heuristics on the performance of a genetic algorithm for the school timetabling problem

Raghavjee

Pillay

2011

Proceedings of the South African Institute of Computer Scientists and Information Technologists Conference on Knowledge, Innova

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This paper examines the effect of using construction heuristics on the evolutionary process for the domain of school timetabling. The paper firstly presents a genetic algorithm to solve the school timetabling problem. The paper compares the performance of a GA with randomly creating potential solutions in the initial population with that of a GA using a construction heuristic for developing the initial solutions. Two construction heuristics, namely, largest degree and saturation degree are studied. The GA's are applied to a data set of six real world problems made available for the Greek school timetabling problem. This study has revealed that the use of construction heuristics improves the performance of the GA to produce better quality timetables. Furthermore, different construction heuristics produce better results for different problems.

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Section: Introductionmentioning

confidence: 99%