Differential Evolution with a local search operator
GU Ji-rong, Guojun Gu · 2010
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.