NDLI: Adapting immune system based algorithms for class timetabling

Content Provider	IEEE Xplore Digital Library
Author	Malim, M.R.
Copyright Year	2010
Description	Author affiliation: Faculty of Computer and Mathematical Sciences University Technology MARA 40450 Shah Alam, Selangor, Malaysia (Malim, M.R.)
Abstract	Class timetabling is a highly constrained problem. Metaheuristic approaches have successfully been applied to solve the problem. This paper presents three immune system based algorithms for class timetabling; clonal selection, immune network, and negative selection. The ultimate goal is to show that the immune based algorithms may be adapted as new alternatives for solving class timetabling problems. The algorithms have been implemented on benchmark datasets. Experimental results have shown that all algorithms are good optimization algorithms. The algorithms are compared based on fitness values, relative robustness, and CPU times. Tests of hypotheses have significantly shown that the immune network is more effective than the other two algorithms. All algorithms can handle the hard and soft constraints very well. The values of relative robustness have shown that the timetables produced by clonal selection are more robust compared to the other two algorithms. The recorded CPU times have revealed that the immune network has acquired the longest time on all datasets. A comparison with published results has shown that all algorithms are as good as other solution methods. For future work, these algorithms will be employed to other domains of timetabling problems.
Starting Page	215
Ending Page	222
File Size	1707086
Page Count	8
File Format	PDF
ISBN	9781424456505
DOI	10.1109/INFRKM.2010.5466914
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Timetabling Problem Multidimensional systems Artificial Intelligence Evolutionary computation Artificial Immune System Constraint optimization Processor scheduling Artificial immune systems Biology computing Benchmark testing Robustness Artificial intelligence Immune system
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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