Modifying Regeneration Mutation and Hybridising Clonal Selection for Evolutionary Algorithms Based Timetabling Tool
Joint Authors
Thepphakorn, Thatchai
Pongcharoen, Pupong
Hicks, Chris
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-04
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
This paper outlines the development of a new evolutionary algorithms based timetabling (EAT) tool for solving course scheduling problems that include a genetic algorithm (GA) and a memetic algorithm (MA).
Reproduction processes may generate infeasible solutions.
Previous research has used repair processes that have been applied after a population of chromosomes has been generated.
This research developed a new approach which (i) modified the genetic operators to prevent the creation of infeasible solutions before chromosomes were added to the population; (ii) included the clonal selection algorithm (CSA); and the elitist strategy (ES) to improve the quality of the solutions produced.
This approach was adopted by both the GA and MA within the EAT.
The MA was further modified to include hill climbing local search.
The EAT program was tested using 14 benchmark timetabling problems from the literature using a sequential experimental design, which included a fractional factorial screening experiment.
Experiments were conducted to (i) test the performance of the proposed modified algorithms; (ii) identify which factors and interactions were statistically significant; (iii) identify appropriate parameters for the GA and MA; and (iv) compare the performance of the various hybrid algorithms.
The genetic algorithm with modified genetic operators produced an average improvement of over 50%.
American Psychological Association (APA)
Thepphakorn, Thatchai& Pongcharoen, Pupong& Hicks, Chris. 2015. Modifying Regeneration Mutation and Hybridising Clonal Selection for Evolutionary Algorithms Based Timetabling Tool. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1074869
Modern Language Association (MLA)
Thepphakorn, Thatchai…[et al.]. Modifying Regeneration Mutation and Hybridising Clonal Selection for Evolutionary Algorithms Based Timetabling Tool. Mathematical Problems in Engineering No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1074869
American Medical Association (AMA)
Thepphakorn, Thatchai& Pongcharoen, Pupong& Hicks, Chris. Modifying Regeneration Mutation and Hybridising Clonal Selection for Evolutionary Algorithms Based Timetabling Tool. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1074869
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074869