Title : ( Course timetabling using evolutionary operators )
Authors: Danial Qaurooni , Mohammad Reza Akbarzadeh Totonchi ,Access to full-text not allowed by authors
Abstract
Timetabling is the problem of scheduling a set of events while satisfying various constraints. In this paper, we develop and study the performance of an evolutionary algorithm, designed to solve a specific variant of the timetabling problem. Our aim here is twofold: to develop a competitive algorithm, but more importantly, to investigate the applicability of evolutionary operators to timetabling. To this end, the introduced algorithm is tested using a benchmark set. Comparison with other algorithms shows that it achieves better results in some, but not all instances, signifying strong and weak points. To further the study, more comprehensive tests are performed in connection with another evolutionary algorithm that uses strictly group-based operators. Our analysis of the empirical results leads us to question single-level selection, proposing, in its place, a multi-level alternative
Keywords
, Combinatorial optimization, Scheduling and timetabling, Evolutionary operators, Memetic algorithms Grouping genetic algorithms@article{paperid:1045457,
author = {Danial Qaurooni and Akbarzadeh Totonchi, Mohammad Reza},
title = {Course timetabling using evolutionary operators},
journal = {Applied Soft Computing},
year = {2013},
volume = {13},
number = {5},
month = {July},
issn = {1568-4946},
pages = {2504--2514},
numpages = {10},
keywords = {Combinatorial optimization، Scheduling and timetabling، Evolutionary operators، Memetic algorithms
Grouping genetic algorithms},
}
%0 Journal Article
%T Course timetabling using evolutionary operators
%A Danial Qaurooni
%A Akbarzadeh Totonchi, Mohammad Reza
%J Applied Soft Computing
%@ 1568-4946
%D 2013