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A simple strategy for maintaining diversity and reducing crowding in differential evolution


Montgomery, J and Chen, S, A simple strategy for maintaining diversity and reducing crowding in differential evolution, Proceedings of 2012 IEEE Congress on Evolutionary Computation, 10-15 June 2012, Brisbane, Australia, pp. 2692-2699. ISBN 978-1-4673-1510-4 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/CEC.2012.6252891


Differential evolution (DE) is a widely-effective population-based continuous optimiser that requires convergence to automatically scale its moves. However, once its population has begun to converge its ability to conduct global search is diminished, as the difference vectors used to generate new solutions are derived from the current population membersí positions. In multi-modal search spaces DE may converge too rapidly, i.e., before adequately exploring the search space to identify the best region(s) in which to conduct its finer-grained search. Traditional crowding or niching techniques can be computationally costly or fail to compare new solutions with the most appropriate existing population member. This paper proposes a simple intervention strategy that compares each new solution with the population member it is most likely to be near, and prevents those moves that are below a threshold that decreases over the algorithmís run, allowing the algorithm to ultimately converge. Comparisons with a standard DE algorithm on a number of multi-modal problems indicate that the proposed technique can achieve real and sizable improvements.

Item Details

Item Type:Refereed Conference Paper
Research Division:Information and Computing Sciences
Research Group:Machine learning
Research Field:Neural networks
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Montgomery, J (Dr James Montgomery)
ID Code:92143
Year Published:2012
Deposited By:Information and Communication Technology
Deposited On:2014-06-06
Last Modified:2018-03-14

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