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Type: Conference paper
Title: A repair method for differential evolution with combined variants to solve dynamic constrained optimization problems
Author: Ameca-Alducin, M.
Mezura-Montes, E.
Cruz-Ramírez, N.
Citation: Proceedings of the Annual Conference on Genetic and Evolutionary Computation (GECCO 2015), 2015 / pp.241-248
Publisher: Association for Computing Machinery
Publisher Place: New York, USA
Issue Date: 2015
ISBN: 1450334725
Conference Name: Annual Conference on Genetic and Evolutionary Computation (GECCO 2015) (11 Jul 2015 - 15 Jul 2015 : Madrid, Spain)
Statement of
María-Yaneli Ameca-Alducin, Efrén Mezura-Montes and Nicandro Cruz-Ramírez
Abstract: Repair methods, which usually require feasible solutions as reference, have been employed by Evolutionary Algorithms to solve constrained optimization problems. In this work, a novel repair method, which does not require feasible solutions as reference and inspired by the differential mutation, is added to an algorithm which uses two variants of differential evolution to solve dynamic constrained optimization problems. The proposed repair method replaces a local search operator with the aim to improve the overall performance of the algorithm in different frequencies of change in the constrained space. The proposed approach is compared against other recently proposed algorithms in an also recently proposed benchmark. The results show that the proposed improved algorithm outperforms its original version and provides a very competitive overall performance with different change frequencies.
Keywords: Differential Evolution; constraint-handling; dynamic optimization
Rights: © 2015 ACM
RMID: 0030067304
DOI: 10.1145/2739480.2754786
Appears in Collections:Computer Science publications

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