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|Title:||A repair method for differential evolution with combined variants to solve dynamic constrained optimization problems|
|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|
|Conference Name:||Annual Conference on Genetic and Evolutionary Computation (GECCO 2015) (11 Jul 2015 - 15 Jul 2015 : Madrid, Spain)|
|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|
|Appears in Collections:||Computer Science publications|
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