Welcome to the InfoSci Platform
Reference Hub3
Parallel Scatter Search Algorithms for Exam Timetabling

Parallel Scatter Search Algorithms for Exam Timetabling

Nashat Mansour, Ghia Sleiman-Haidar
Copyright: © 2011 |Volume: 2 |Issue: 3 |Pages: 18
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781613505694|DOI: 10.4018/jamc.2011070102
Cite Article Cite Article

MLA

Mansour, Nashat, and Ghia Sleiman-Haidar. "Parallel Scatter Search Algorithms for Exam Timetabling." IJAMC vol.2, no.3 2011: pp.27-44. http://doi.org/10.4018/jamc.2011070102

APA

Mansour, N. & Sleiman-Haidar, G. (2011). Parallel Scatter Search Algorithms for Exam Timetabling. International Journal of Applied Metaheuristic Computing (IJAMC), 2(3), 27-44. http://doi.org/10.4018/jamc.2011070102

Chicago

Mansour, Nashat, and Ghia Sleiman-Haidar. "Parallel Scatter Search Algorithms for Exam Timetabling," International Journal of Applied Metaheuristic Computing (IJAMC) 2, no.3: 27-44. http://doi.org/10.4018/jamc.2011070102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

University exam timetabling refers to scheduling exams into predefined days, time periods and rooms, given a set of constraints. Exam timetabling is a computationally intractable optimization problem, which requires heuristic techniques for producing adequate solutions within reasonable execution time. For large numbers of exams and students, sequential algorithms are likely to be time consuming. This paper presents parallel scatter search meta-heuristic algorithms for producing good sub-optimal exam timetables in a reasonable time. Scatter search is a population-based approach that generates solutions over a number of iterations and aims to combine diversification and search intensification. The authors propose parallel scatter search algorithms that are based on distributing the population of candidate solutions over a number of processors in a PC cluster environment. The main components of scatter search are computed in parallel and efficient communication techniques are employed. Empirical results show that the proposed parallel scatter search algorithms yield good speed-up. Also, they show that parallel scatter search algorithms improve solution quality because they explore larger parts of the search space within reasonable time, in contrast with the sequential algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.