Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/14278
Title: Swarm Intelligence for Educational Timetabling A Systematic Literature Review
Authors: Omer Ahmed Elbashir ElhagMusa
Keywords: Systematic Literature
Issue Date: 2018
Publisher: Neelain University
Abstract: Abstract Educational timetabling problems regardless of their classification are complex combinatorial problems that face many educational institutions. These problems require the satisfaction of a set of constraints to attain an efficient solution in the matter of resources and time consumption. Swarm intelligence techniques have been successfully applied to solve educational timetabling problems. In this thesis, the swarm intelligence solutions for solving educational timetabling problems are investigated and critically discussed. The thesis reports the implementation and results of a systematic literature review (SLR) used to collect and highlight scientific literature on swarm intelligence for educational timetabling problems. The research presents in detail the problem of educational timetabling and its variances. In addition, datasets and standard benchmark instances used in educational timetabling experiments are also highlighted. Moreover, a new taxonomy classification along with a database concerned with educational timetabling problems, swarm intelligence solutions, and common issues in educational timetabling is developed as a research contribution in the thesis. The research links related areas and discusses hot topics on the efficiency of using swarm intelligence techniques in educational timetabling; and filling the gap between academic results and industry implementation in educational timetabling. Additionally, comparisons of the results obtained fiom the systematic literature review are presented. Finally, this thesis suggests promising directions and recommendations for future research.
Description: Thesis submitted to Neelian University for the degree of Master in Computer Science
URI: http://hdl.handle.net/123456789/14278
Appears in Collections:Masters theses : Computer Science

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