Differential evolution with a local search operator

Authors:
Jirong Gu;Guojun Gu
Affiliations:
Geography and Resources Sciences College, Sichuan Normal University, Chengdu, China;School of Physics, Tianjin Normal University, Tianjin, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
Year:
2010

Citing 6
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Abstract

Differential Evolution (DE) is a population-based stochastic search algorithm, which has shown good performance in many optimization problems. In this paper, we propose an improved DE algorithm, called LSDE, by using a local search operator to enhance the performance of classical DE. In order to verify the performance of LSDE, we test the proposed approach on seven well-known benchmark problems. The simulation results show that LSDE obtains good performance and outperforms the classical DE in all test cases.