UPM Institutional Repository

Evaluating premature convergence for metaheuristic.


Citation

Md Sultan, Abu Bakar and Abdullah, Azizol and Mahmod, Ramlan and Abdullah @ Selimun, Mohd Taufik (2008) Evaluating premature convergence for metaheuristic. International Journal of Computer Science and Engineering System, 2 (3). pp. 187-188. ISSN 0973-4406

Abstract

Premature convergence is a common problem to population based metaheurustic. The evaluation of premature convergence rate is difficult to obtain because the stochastic nature of metaheuristic. This paper presents a statistical effort to evaluate and predict the premature rate and performance of metaheuristic. The Fitness Distance Correlation technique was used to determine the premature rate and the memetic algorithm is tested on five selected timetabling datasets. The results shows that using relatively less effort, we can gain meaningful values of premature problems.


Download File

[img]
Preview
PDF (Abstract)
Evaluating premature convergence for metaheuristic.pdf

Download (83kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Publisher: Serials Publications
Keywords: Premature convergence; Metaheuristic; Fitness distance correlation.
Depositing User: Nida Hidayati Ghazali
Date Deposited: 14 May 2014 08:01
Last Modified: 23 Oct 2015 08:12
URI: http://psasir.upm.edu.my/id/eprint/14584
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item