Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem

Genetic algorithm (GA) approach is one of an evolutionary optimization technique relies on natural selection. The employment of GA still popular and it was applied to many real-world problems, especially in many combinatorial optimization solutions. Lecturer Timetabling Problem (LTP) has been resear...

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Published in:Indonesian Journal of Electrical Engineering and Computer Science
Main Author: Yusoff M.; Othman A.A.
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051247636&doi=10.11591%2fijeecs.v12.i1.pp303-309&partnerID=40&md5=cbb19fb32db62e449dbc8bde12736ba9
id 2-s2.0-85051247636
spelling 2-s2.0-85051247636
Yusoff M.; Othman A.A.
Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
2018
Indonesian Journal of Electrical Engineering and Computer Science
12
1
10.11591/ijeecs.v12.i1.pp303-309
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051247636&doi=10.11591%2fijeecs.v12.i1.pp303-309&partnerID=40&md5=cbb19fb32db62e449dbc8bde12736ba9
Genetic algorithm (GA) approach is one of an evolutionary optimization technique relies on natural selection. The employment of GA still popular and it was applied to many real-world problems, especially in many combinatorial optimization solutions. Lecturer Timetabling Problem (LTP) has been researched for a few decades and produced good solutions. Although, some of LTP offers good results, the criteria and constraints of each LTP however are different from other universities. The LTP appears to be a tiresome job to the scheduler that involves scheduling of students, classes, lecturers and rooms at specific time-slots while satisfying all the necessary requirements to build a feasible timetable. This paper addresses the employment and evaluation of GA to overcome the biggest challenge in LTP to find clashes-free slots for lecturer based on a case study in the Faculty of Computer and Mathematical Sciences, University Technologi MARA, Malaysia. Hence, the performance of the GA is evaluated based on selection, mutation and crossover using different number of population size. A comparison of performance between simple GA with Tournament Selection scheme combined with Elitism (TE) and a GA with Tournament (T) selection scheme. The findings demonstrate that the embedded penalty measures and elitism composition provide good performance that satisfies all the constraints in producing timetables to lecturers. © 2018 Institute of Advanced Engineering and Science All rights reserved.
Institute of Advanced Engineering and Science
25024752
English
Article

author Yusoff M.; Othman A.A.
spellingShingle Yusoff M.; Othman A.A.
Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
author_facet Yusoff M.; Othman A.A.
author_sort Yusoff M.; Othman A.A.
title Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
title_short Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
title_full Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
title_fullStr Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
title_full_unstemmed Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
title_sort Genetic algorithm with elitist-tournament for clashes-free slots of lecturer timetabling problem
publishDate 2018
container_title Indonesian Journal of Electrical Engineering and Computer Science
container_volume 12
container_issue 1
doi_str_mv 10.11591/ijeecs.v12.i1.pp303-309
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051247636&doi=10.11591%2fijeecs.v12.i1.pp303-309&partnerID=40&md5=cbb19fb32db62e449dbc8bde12736ba9
description Genetic algorithm (GA) approach is one of an evolutionary optimization technique relies on natural selection. The employment of GA still popular and it was applied to many real-world problems, especially in many combinatorial optimization solutions. Lecturer Timetabling Problem (LTP) has been researched for a few decades and produced good solutions. Although, some of LTP offers good results, the criteria and constraints of each LTP however are different from other universities. The LTP appears to be a tiresome job to the scheduler that involves scheduling of students, classes, lecturers and rooms at specific time-slots while satisfying all the necessary requirements to build a feasible timetable. This paper addresses the employment and evaluation of GA to overcome the biggest challenge in LTP to find clashes-free slots for lecturer based on a case study in the Faculty of Computer and Mathematical Sciences, University Technologi MARA, Malaysia. Hence, the performance of the GA is evaluated based on selection, mutation and crossover using different number of population size. A comparison of performance between simple GA with Tournament Selection scheme combined with Elitism (TE) and a GA with Tournament (T) selection scheme. The findings demonstrate that the embedded penalty measures and elitism composition provide good performance that satisfies all the constraints in producing timetables to lecturers. © 2018 Institute of Advanced Engineering and Science All rights reserved.
publisher Institute of Advanced Engineering and Science
issn 25024752
language English
format Article
accesstype
record_format scopus
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