Citation

Shaker, K; Abdullah, S and Alqudsi, A Bacteria Swarm Optimisation Approach for Enrolment-Based Course Timetabling Problems. In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic, pages 515-525, 2015.

Paper


Abstract

The university course timetabling problem is known as a NP-hard problem. It is also sometimes known as a class/teacher timetabling that refers to a set of courses that need to be scheduled into a given number of rooms and timeslots within a week and, at the same time, students and teachers are assigned to courses so that the meetings can take place. A novel population based approach is proposed in this paper called a Bacteria Swarm Optimisation (BSO) algorithm. BSO is developed based on the behavior of bacteria when it searches for the nutrients. The search space is divided into three regions namely, risk, null and rich regions. Differential Evolution algorithm (DE) is embedded within BSO to move the solutions toward the best solution. The performance of our approach is tested over eleven benchmark datasets (representing one large, five medium and five small problems). Experimental results show that our approach is able to generate competitive results when compared with previous available approaches. Possible extensions upon this simple approach are also discussed.


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Bibtex

@INPROCEEDINGS{2015-515-525-P, author = {K. Shaker and S. Abdullah and A. Alqudsi },
title = {Bacteria Swarm Optimisation Approach for Enrolment-Based Course Timetabling Problems },
booktitle = {In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic},
year = {2015},
editor = {Z. Hanzalek and G. Kendall and B. McCollum and P. Sucha},
pages = {515--525},
note = {Paper},
abstract = { The university course timetabling problem is known as a NP-hard problem. It is also sometimes known as a class/teacher timetabling that refers to a set of courses that need to be scheduled into a given number of rooms and timeslots within a week and, at the same time, students and teachers are assigned to courses so that the meetings can take place. A novel population based approach is proposed in this paper called a Bacteria Swarm Optimisation (BSO) algorithm. BSO is developed based on the behavior of bacteria when it searches for the nutrients. The search space is divided into three regions namely, risk, null and rich regions. Differential Evolution algorithm (DE) is embedded within BSO to move the solutions toward the best solution. The performance of our approach is tested over eleven benchmark datasets (representing one large, five medium and five small problems). Experimental results show that our approach is able to generate competitive results when compared with previous available approaches. Possible extensions upon this simple approach are also discussed. },
owner = {Graham},
timestamp = {2017.01.16},
webpdf = {2015-515-525-P.pdf} }