Citation

Sabar, N. R; Ayob, M and Kendall, G Solving Examination Timetabling Problems using Honey-bee Mating Optimization (ETP-HBMO). Proceedings of the 4th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA 2009), 10-12 Aug 2009, Dublin, Ireland, pages 399-408, 2009.

Paper


Abstract

Examination timetabling problems deal with assigning a set of exams into a limited number of timeslots, whilst satisfying a set of constraints. In this work, we propose ETP-HBMO (Examination Timetabling Problems-Honey-bee Mating Optimization) algorithm for solving examination timetabling problems. The honey-bee mating process is considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. The mating process (i.e. generating a new solution) of the queen (current best solution) begins when the queen leaves the nest to perform a mating flight during which time the drones (trial solutions) follow the queen and mate with her. In this work, we test ETP-HBMO on Carterís un-capacitated benchmark examination timetable dataset and evaluate the performance using standard proximity costs. Results demonstrate that the performance of the Honey-bee Mating Optimization Algorithm is comparable with the results of other methodologies that have been reported in the literature over recent years. Indeed, ETP-HBMO outperformed other approaches on a few instances. This indicates that ETP-HBMO is effective in solving examination timetabling problems, and worthy of further research.


pdf

You can download the pdf of this publication from here


doi

This publication does not have a doi, so we cannot provide a link to the original source

What is a doi?: A doi (Document Object Identifier) is a unique identifier for sicientific papers (and occasionally other material). This provides direct access to the location where the original article is published using the URL http://dx.doi/org/xxxx (replacing xxx with the doi). See http://dx.doi.org/ for more information



URL

This pubication does not have a URL associated with it.

The URL is only provided if there is additional information that might be useful. For example, where the entry is a book chapter, the URL might link to the book itself.


Bibtex

@INPROCEEDINGS{2009-399-408-P, author = {N. R. Sabar and M. Ayob and G. Kendall},
title = {Solving Examination Timetabling Problems using Honey-bee Mating Optimization (ETP-HBMO)},
booktitle = {Proceedings of the 4th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA 2009), 10-12 Aug 2009, Dublin, Ireland},
year = {2009},
editor = {J. Blazewicz and M. Drozdowski and G. Kendall and B. McCollum},
pages = {399--408},
note = {Paper},
abstract = {Examination timetabling problems deal with assigning a set of exams into a limited number of timeslots, whilst satisfying a set of constraints. In this work, we propose ETP-HBMO (Examination Timetabling Problems-Honey-bee Mating Optimization) algorithm for solving examination timetabling problems. The honey-bee mating process is considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. The mating process (i.e. generating a new solution) of the queen (current best solution) begins when the queen leaves the nest to perform a mating flight during which time the drones (trial solutions) follow the queen and mate with her. In this work, we test ETP-HBMO on Carterís un-capacitated benchmark examination timetable dataset and evaluate the performance using standard proximity costs. Results demonstrate that the performance of the Honey-bee Mating Optimization Algorithm is comparable with the results of other methodologies that have been reported in the literature over recent years. Indeed, ETP-HBMO outperformed other approaches on a few instances. This indicates that ETP-HBMO is effective in solving examination timetabling problems, and worthy of further research.},
owner = {gxk},
timestamp = {2010.10.11},
webpdf = {2009-399-408-P.pdf} }