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μJADE: adaptive differential evolution with a small population

Brown, C, Jin, Y, Leach, M and Hodgson, M (2015) μJADE: adaptive differential evolution with a small population Soft Computing.

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Abstract

This paper proposes a new differential evolution (DE) algorithm for unconstrained continuous optimisation problems, termed (Formula presented.)JADE, that uses a small or ‘micro’ ((Formula presented.)) population. The main contribution of the proposed DE is a new mutation operator, ‘current-by-rand-to-pbest.’ With a population size less than 10, (Formula presented.)JADE is able to solve some classical multimodal benchmark problems of 30 and 100 dimensions as reliably as some state-of-the-art DE algorithms using conventionally sized populations. The algorithm also compares favourably to other small population DE variants and classical DE.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Centre for Environmental Strategy
Authors :
AuthorsEmailORCID
Brown, CUNSPECIFIEDUNSPECIFIED
Jin, YUNSPECIFIEDUNSPECIFIED
Leach, MUNSPECIFIEDUNSPECIFIED
Hodgson, MUNSPECIFIEDUNSPECIFIED
Date : 27 June 2015
Identification Number : 10.1007/s00500-015-1746-x
Additional Information : The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1746-x
Depositing User : Symplectic Elements
Date Deposited : 14 Oct 2015 10:51
Last Modified : 27 Jun 2016 01:08
URI: http://epubs.surrey.ac.uk/id/eprint/808883

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