Faculty timetabling using genetic algorithm

Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs...

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Main Author: Liong, Boon Yaun
Format: Undergraduates Project Papers
Language:English
Published: 2011
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/4253/
http://umpir.ump.edu.my/id/eprint/4253/
http://umpir.ump.edu.my/id/eprint/4253/1/LIONG_BOON_YAUN.PDF
id ump-4253
recordtype eprints
spelling ump-42532015-03-03T09:17:56Z http://umpir.ump.edu.my/id/eprint/4253/ Faculty timetabling using genetic algorithm Liong, Boon Yaun QA Mathematics Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%. 2011-05 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4253/1/LIONG_BOON_YAUN.PDF Liong, Boon Yaun (2011) Faculty timetabling using genetic algorithm. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:67966&theme=UMP2
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA Mathematics
spellingShingle QA Mathematics
Liong, Boon Yaun
Faculty timetabling using genetic algorithm
description Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.
format Undergraduates Project Papers
author Liong, Boon Yaun
author_facet Liong, Boon Yaun
author_sort Liong, Boon Yaun
title Faculty timetabling using genetic algorithm
title_short Faculty timetabling using genetic algorithm
title_full Faculty timetabling using genetic algorithm
title_fullStr Faculty timetabling using genetic algorithm
title_full_unstemmed Faculty timetabling using genetic algorithm
title_sort faculty timetabling using genetic algorithm
publishDate 2011
url http://umpir.ump.edu.my/id/eprint/4253/
http://umpir.ump.edu.my/id/eprint/4253/
http://umpir.ump.edu.my/id/eprint/4253/1/LIONG_BOON_YAUN.PDF
first_indexed 2023-09-18T21:58:45Z
last_indexed 2023-09-18T21:58:45Z
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