Journal
APPLIED INTELLIGENCE
Volume 29, Issue 3, Pages 228-247Publisher
SPRINGER
DOI: 10.1007/s10489-007-0091-x
Keywords
Differential evolution; Control parameter; Fitness function; Global function optimization; Self-adaptation; Population size
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This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.
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