2020
DOI: 10.1109/access.2020.2964222
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Advanced Cauchy Mutation for Differential Evolution in Numerical Optimization

Abstract: Among many evolutionary algorithms, differential evolution (DE) has received much attention over the last two decades. DE is a simple yet powerful evolutionary algorithm that has been used successfully to optimize various real-world problems. Since it was introduced, many researchers have developed new methods for DE, and one of them makes use of a mutation based on the Cauchy distribution to increase the convergence speed of DE. The method monitors the results of each individual in the selection operator and … Show more

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Cited by 31 publications
(10 citation statements)
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“…Choi and Lee [19] proposed an ex-tended self-adaptive differential evolution algorithm which increases the greediness of jDE algorithm searchability. Choi et al [20] developed a sigmoid-based parameter control in order to alternate the failure threshold for performing the Cauchy mutation. In this case, the proposed algorithm, which advances the Cauchy mutation, can establish a good ratio between exploration and exploitation.…”
Section: Mde Algorithmmentioning
confidence: 99%
“…Choi and Lee [19] proposed an ex-tended self-adaptive differential evolution algorithm which increases the greediness of jDE algorithm searchability. Choi et al [20] developed a sigmoid-based parameter control in order to alternate the failure threshold for performing the Cauchy mutation. In this case, the proposed algorithm, which advances the Cauchy mutation, can establish a good ratio between exploration and exploitation.…”
Section: Mde Algorithmmentioning
confidence: 99%
“…Liu et al (2020) presented a differential evolution algorithm with a new encoding mechanism and Cauchy mutation for optimizing large unequally spaced planar array layouts with the minimum element spacing constraint. Choi et al (2020) proposed a sigmoid based parameter control that alters the failure threshold for performing the Cauchy mutation in a time-varying schedule, which can establish a good ratio between exploration and exploitation. Wang et al (2020) proposed a yin-yang firefly algorithm based on dimensionally Cauchy mutation for performance improvement of FA.…”
Section: Introductionmentioning
confidence: 99%
“…Success-history based adaptive differential evolution (SHADE) [13] further enhanced JADE which records a series of F and CR for learning strategy. Choi et al [14] proposed a sigmoid based control of parameters that changes the threshold for operating the Cauchy mutation dynamically, which balances exploration and exploitation ability. Moreover, integrating various mutation strategies and a handful of parameter settings are promising research directions, variants in this kind include CoDE [15] with composite generation strategies and parameter settings, EPSDE [16], MPEDE [17] and its variant EDEV [18] which ensembles diverse DE variants from a high level.…”
Section: Introductionmentioning
confidence: 99%