Improved differential evolution with dynamic population size

Authors:
Fuzhuo Huang;Ling Wang;Bo Liu
Affiliations:
Department of Automation, Tsinghua University, Beijing, China;Department of Automation, Tsinghua University, Beijing, China;Department of Automation, Tsinghua University, Beijing, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

Citing 2
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Abstract

As a novel evolutionary computing technique, recently Differential Evolution (DE) has attracted much attention and wide applications due to its simple concept and easy implementation. However, all the control parameters of the classic DE (crossover rate, scaling factor, and population size) keep fixed during the searching process. To improve the performance of DE, an improved DE (IDE) with dynamic population size is proposed in this paper. Simulation results and comparisons based on some well-known benchmarks and an IIR design problem show the good efficiency of the proposed IDE.