Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique
There are many timetabling problem are studied by researchers such as the Toronto dataset, Dataset of University of Melbourne, Dataset of University of Nottingham as well as the dataset from the local University such as Dataset of University Kebangsaan Malaysia(UKM) and Dataset of University Teknol...
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ump-120442016-03-17T02:04:12Z http://umpir.ump.edu.my/id/eprint/12044/ Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique Lee, Kia Wei QA76 Computer software There are many timetabling problem are studied by researchers such as the Toronto dataset, Dataset of University of Melbourne, Dataset of University of Nottingham as well as the dataset from the local University such as Dataset of University Kebangsaan Malaysia(UKM) and Dataset of University Teknologi MARA(IJiTM). For this thesis, we are concerning on solving the Second International Timetabling Competition (1TC2007) dataset. The 1TC2007 dataset is chosen because it has additional hard constraints and, software constraints compared to other datasets. Besides, 1TC2007 consists of 12 datasets with different features in the terms of number of exams, number of room and number of timeslot. We are choosing the Late Acceptance Hill Climbing method to solve this dataset. The reason why using Late Acceptance Hill Climbing is due to the Late Acceptance Hill Climbing is an effective and simple method that will ease the implementation. 2014 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/12044/1/LEE%20KIA%20WEI.PDF Lee, Kia Wei (2014) Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique. Faculty of Computer System and Software Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:92145&theme=UMP2 |
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QA76 Computer software Lee, Kia Wei Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
description |
There are many timetabling problem are studied by researchers such as the Toronto dataset, Dataset of University of Melbourne, Dataset of University of
Nottingham as well as the dataset from the local University such as Dataset of University Kebangsaan Malaysia(UKM) and Dataset of University Teknologi
MARA(IJiTM). For this thesis, we are concerning on solving the Second International Timetabling Competition (1TC2007) dataset. The 1TC2007 dataset is chosen because
it has additional hard constraints and, software constraints compared to other datasets. Besides, 1TC2007 consists of 12 datasets with different features in the terms of number of exams, number of room and number of timeslot. We are choosing the Late Acceptance Hill Climbing method to solve this dataset. The reason why using Late Acceptance Hill Climbing is due to the Late Acceptance Hill Climbing is an effective and simple method that will ease the implementation. |
format |
Undergraduates Project Papers |
author |
Lee, Kia Wei |
author_facet |
Lee, Kia Wei |
author_sort |
Lee, Kia Wei |
title |
Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
title_short |
Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
title_full |
Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
title_fullStr |
Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
title_full_unstemmed |
Solving the ITC2007 examination timetabling problem by using the late acceptance hill climbing technique |
title_sort |
solving the itc2007 examination timetabling problem by using the late acceptance hill climbing technique |
publishDate |
2014 |
url |
http://umpir.ump.edu.my/id/eprint/12044/ http://umpir.ump.edu.my/id/eprint/12044/ http://umpir.ump.edu.my/id/eprint/12044/1/LEE%20KIA%20WEI.PDF |
first_indexed |
2023-09-18T22:13:14Z |
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2023-09-18T22:13:14Z |
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