Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement
The paper investigates a partial exam assignment approach for solving the examination timetabling problem. Current approaches involve scheduling all of the exams into time slots and rooms (i.e., produce an initial solution) and then continuing by improving the initial solution in a predetermined num...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-05-01
|
Series: | Computation |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-3197/8/2/46 |
id |
doaj-a9eea8a2d9f64ee58d529d968542624d |
---|---|
record_format |
Article |
spelling |
doaj-a9eea8a2d9f64ee58d529d968542624d2020-11-25T02:15:29ZengMDPI AGComputation2079-31972020-05-018464610.3390/computation8020046Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and ImprovementAshis Kumar Mandal0M. N. M. Kahar1Graham Kendall2Graduate School of Software & Information Science, Iwate Prefectural University, Iwate 020-0693, JapanFaculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, Kuantan 25000, Pahang, MalaysiaUniversity of Nottingham Malaysia Campus, Semenyih, Selangor 43500, MalaysiaThe paper investigates a partial exam assignment approach for solving the examination timetabling problem. Current approaches involve scheduling all of the exams into time slots and rooms (i.e., produce an initial solution) and then continuing by improving the initial solution in a predetermined number of iterations. We propose a modification of this process that schedules partially selected exams into time slots and rooms followed by improving the solution vector of partial exams. The process then continues with the next batch of exams until all exams are scheduled. The partial exam assignment approach utilises partial graph heuristic orderings with a modified great deluge algorithm (PGH-mGD). The PGH-mGD approach is tested on two benchmark datasets, a capacitated examination dataset from the 2nd international timetable competition (ITC2007) and an un-capacitated Toronto examination dataset. Experimental results show that PGH-mGD is able to produce quality solutions that are competitive with those of the previous approaches reported in the scientific literature.https://www.mdpi.com/2079-3197/8/2/46examination timetabling problemgraph heuristic orderingsgreat deluge algorithmmeta-heuristics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ashis Kumar Mandal M. N. M. Kahar Graham Kendall |
spellingShingle |
Ashis Kumar Mandal M. N. M. Kahar Graham Kendall Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement Computation examination timetabling problem graph heuristic orderings great deluge algorithm meta-heuristics |
author_facet |
Ashis Kumar Mandal M. N. M. Kahar Graham Kendall |
author_sort |
Ashis Kumar Mandal |
title |
Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement |
title_short |
Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement |
title_full |
Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement |
title_fullStr |
Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement |
title_full_unstemmed |
Addressing Examination Timetabling Problem Using a Partial Exams Approach in Constructive and Improvement |
title_sort |
addressing examination timetabling problem using a partial exams approach in constructive and improvement |
publisher |
MDPI AG |
series |
Computation |
issn |
2079-3197 |
publishDate |
2020-05-01 |
description |
The paper investigates a partial exam assignment approach for solving the examination timetabling problem. Current approaches involve scheduling all of the exams into time slots and rooms (i.e., produce an initial solution) and then continuing by improving the initial solution in a predetermined number of iterations. We propose a modification of this process that schedules partially selected exams into time slots and rooms followed by improving the solution vector of partial exams. The process then continues with the next batch of exams until all exams are scheduled. The partial exam assignment approach utilises partial graph heuristic orderings with a modified great deluge algorithm (PGH-mGD). The PGH-mGD approach is tested on two benchmark datasets, a capacitated examination dataset from the 2nd international timetable competition (ITC2007) and an un-capacitated Toronto examination dataset. Experimental results show that PGH-mGD is able to produce quality solutions that are competitive with those of the previous approaches reported in the scientific literature. |
topic |
examination timetabling problem graph heuristic orderings great deluge algorithm meta-heuristics |
url |
https://www.mdpi.com/2079-3197/8/2/46 |
work_keys_str_mv |
AT ashiskumarmandal addressingexaminationtimetablingproblemusingapartialexamsapproachinconstructiveandimprovement AT mnmkahar addressingexaminationtimetablingproblemusingapartialexamsapproachinconstructiveandimprovement AT grahamkendall addressingexaminationtimetablingproblemusingapartialexamsapproachinconstructiveandimprovement |
_version_ |
1724895977643442176 |