loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Shichen Liu ; Qiwei Lu ; Yan Xiong and Wenchao huang

Affiliation: University of Science and Technology of China, China

ISBN: 978-989-8565-33-4

Keyword(s): Differential Evolution, Numerical Optimization, Parameter Adaptation, Self-adaptation, Replicator Dynamic, Natural Computation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Computational Intelligence ; Enterprise Information Systems ; Evolution Strategies ; Evolutionary Computing ; Game Theory Applications ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Soft Computing

Abstract: Differential Evolution (DE) has been shown to be a simple yet efficient evolutionary algorithm for solving optimization problems in continuous search domain. However the performance of the DE algorithm, to a great extent, depends on the selection of control parameters. In this paper, we propose a Replicator Dynamic Inspired DE algorithm (RDIDE), in which replicator dynamic, a deterministic monotone game dynamic generally used in evolutionary game theory, is introduced to the crossover operator. A new population is generated for an applicable probability distribution of the value of Cr, with which the parameter is evolving as the algorithm goes on and the evolution is rather succinct as well. Therefore, the end-users do not need to find a suitable parameter combination and can solve their problems more simply with our algorithm. Different from the rest of DE algorithms, by replicator dynamic, we obtain an advisable probability distribution of the parameter instead of a certain value o f the parameter. Experiment based on a suite of 10 bound-constrained numerical optimization problems demonstrates that our algorithm has highly competitive performance with respect to several conventional DE and parameter adaptive DE variants. Statistics of the experiment also show that our evolution of the parameter is rational and necessary. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.227.2.246

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Liu, S.; Xiong, Y.; Lu, Q. and huang, W. (2012). Replicator Dynamic Inspired Differential Evolution Algorithm for Global Optimization.In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 133-143. DOI: 10.5220/0004053401330143

@conference{ecta12,
author={Shichen Liu. and Yan Xiong. and Qiwei Lu. and Wenchao huang.},
title={Replicator Dynamic Inspired Differential Evolution Algorithm for Global Optimization},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={133-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004053401330143},
isbn={978-989-8565-33-4},
}

TY - CONF

JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - Replicator Dynamic Inspired Differential Evolution Algorithm for Global Optimization
SN - 978-989-8565-33-4
AU - Liu, S.
AU - Xiong, Y.
AU - Lu, Q.
AU - huang, W.
PY - 2012
SP - 133
EP - 143
DO - 10.5220/0004053401330143

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.