By Topic

Enhancing Differential Evolution frameworks by scale factor local search - Part I

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ville Tirronen ; Department of Mathematical Information Technology, University of Jyväskylä, FI-40014, Finland ; Ferrante Neri ; Tuomo Rossi

This paper proposes a modification of Differential Evolution (DE) schemes. During the offspring generation, a local search is applied, with a certain probability to the scale factor in order to generate an offspring with high performance. In a memetic fashion, the main idea in this paper is that the application of a different perspective in the search of a DE can assist the evolutionary framework and prevent the undesired effect of stagnation which DE is subject to. Two local search algorithms have been tested for this purpose and an application to the individual with the best performance has been proposed. The resulting algorithms seem to significantly enhance the performance of a standard DE scheme over a broad set of test problems. Numerical results show that the modified algorithm is very efficient with respect to a standard DE in terms of final solution detected, convergence speed and robustness.

Published in:

2009 IEEE Congress on Evolutionary Computation

Date of Conference:

18-21 May 2009