Differential Evolution: A Survey of the State-of-the-Art
Citations
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Additional excerpts
...DE is a population-based optimization algorithm for solving complex multi-modal optimization problems [6], [23]....
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Cites background from "Differential Evolution: A Survey of..."
...For a more detailed description of many of the existing variants and major application areas of DE, readers should refer to [43,194,63]....
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1,265 citations
Cites background or methods from "Differential Evolution: A Survey of..."
...In this respect, the first comprehensive survey on almost all aspects of the DE family of algorithms was published in 2011 by [40]....
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...Since then, DE and its variants have emerged as one of the most competitive and versatile family of the evolutionary computing algorithms and have been successfully applied to solve numerous real world problems from diverse domains of science and technology [134,40]....
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...Many DE-variants published subsequently (see [40]) have used this update strategy....
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...The DE family of algorithms commonly uses two crossover methods-exponential (or two-point modulo) and binomial (or uniform) [40]....
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...As was also pointed out in [40], almost eight years back from now, Langdon and Poli [96] made a very interesting study where certain fitness landscapes were evolved with Genetic Programming (GP) to indicate the benefits and weaknesses of a few population-based algorithms like PSO, DE, and CMA-ES....
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References
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