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Population size reduction for the differential evolution algorithm
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DOI：10.1007/s10489-007-0091-x.png)
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Abstract
En 中文
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.
Keywords:
Differential evolution
Control parameter
Fitness function
Global function optimization
Self-adaptation
Population size