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Effect of using neural networks in GA-based school timetabling

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Abstract

The school timetabling problem is a specific kind of timetabling problems. It is characterized by similar sets of subjects used among schools in different years, and by great extent of human factor involved. This particularity lets us to hope existing timetables to be useful information for actual timetabling process, and neural networks to be a suitable technique to assist it. This paper describes experiments on using neural networks as part of the fitness function of a GA-based school timetabling system, the model of what has been proposed by the author earlier. The experimental results show ability of neural networks to be applied for timetable evaluation, as well as reveal various side effects of using neural networks within GA-based school timetabling.

Original languageEnglish
Title of host publicationInternational Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings
EditorsAntonella Cecchi, Nikos Mastorakis
PublisherWorld Scientific and Engineering Academy and Society
Pages117-122
Number of pages6
ISBN (Print)9608457564
Publication statusPublished - 20 Nov 2006
EventProceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS '06 - Venice, Italy
Duration: 20 Nov 200622 Nov 2006

Publication series

NameInternational Conference on Computational Intelligence, Man-Machine Systems and Cybernetics - Proceedings
Volume1

Conference

ConferenceProceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics, CIMMACS '06
Country/TerritoryItaly
CityVenice
Period20/11/0622/11/06

Keywords

  • Fitness Function
  • Genetic Algorithm
  • Neural Networks
  • School Timetabling

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