NDLI: Hybridization Multi-NeighbourhoodParticle Collision Algorithm and Great Deluge for solving course timetabling problems

Content Provider	IEEE Xplore Digital Library
Author	Abuhamdah, A. Ayob, M.
Copyright Year	2009
Description	Author affiliation: Data Mining & Optimization Group (DMO), Centre of Artificial Intelligence Technology (CAIT), Computer Science Department, University Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia (Abuhamdah, A.; Ayob, M.)
Abstract	This work presents a Particle Collision Algorithm (PCA) to solve university course timetabling problems. The aim is to produce an effective algorithm for assigning a set of courses, lecturers and students to a specific number of rooms and timeslots, subject to a set of constraints. The structure of PCA resembles a simulated annealing structure. The basic difference is that PCA does not have cooling schedule and it does not rely on user-defined parameters. PCA differs from Simulated Annealing and other meta-heuristic approaches where, before accepting the trial solution (although we obtain good-quality solution). Therefore, PCA is capable of escaping from local optima. The Hybrid Multi-Neighbourhood Particle Collision Algorithm with Great Deluge using Composite Neighbourhood Structure (HPCA), which it is hybridize the Great Deluge acceptance criterion with PCA and enhances a PCA approach that was originally introduced by Sacco for policy optimization. HPCA differs from basic PCA in terms of applying multi-neighbourhood composite structures, which is divided into two stages, one in the solution construction phase and the other in the improvement phase. HPCA also differs from basic PCA in terms of accepting the worst solution in the scattering phase, which is hybrid the Great Deluge acceptance criterion with PCA. HPCA attempts to further enhance the trial solution by exploring different neighbourhood structures. Results tested on Socha benchmark datasets show that HPCA is able to produce significantly good quality solutions within a reasonable time and outperformed some other approaches in some instances.
Starting Page	108
Ending Page	114
File Size	153049
Page Count	7
File Format	PDF
ISBN	9781424449446
DOI	10.1109/DMO.2009.5341900
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-27
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cooling Particle collisions Great Deluge Data mining NP-complete problem Particle Collision Algorithm Computer science Simulated annealing Particle scattering Benchmark testing Course Timetabling Problem Artificial intelligence Principal component analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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