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  • The influence of used adaptive approach on the performance of algorithm is addressed. Adaptive approaches applied in competitive differential evolution and in differential evolution using an ensemble of mutation strategies and parameter values are compared. The approaches used in these algorithms can be divided into two parts: adaptive mechanism and pool of strategies. Four variants of algorithm combining mutually these two parts are compared experimentally in six benchmark functions at two levels of dimension. It was found that the variants using the pool of ensemble of mutation strategies and parameter values need mostly less number of function evaluation to reach the stopping condition, while the algorithms with pool of competitive differential evolution are more reliable.
  • The influence of used adaptive approach on the performance of algorithm is addressed. Adaptive approaches applied in competitive differential evolution and in differential evolution using an ensemble of mutation strategies and parameter values are compared. The approaches used in these algorithms can be divided into two parts: adaptive mechanism and pool of strategies. Four variants of algorithm combining mutually these two parts are compared experimentally in six benchmark functions at two levels of dimension. It was found that the variants using the pool of ensemble of mutation strategies and parameter values need mostly less number of function evaluation to reach the stopping condition, while the algorithms with pool of competitive differential evolution are more reliable. (en)
Title
  • A Comparison of Two Adaptation Approaches in Differential Evolution
  • A Comparison of Two Adaptation Approaches in Differential Evolution (en)
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  • A Comparison of Two Adaptation Approaches in Differential Evolution
  • A Comparison of Two Adaptation Approaches in Differential Evolution (en)
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  • RIV/61988987:17610/12:A13012OM!RIV13-MSM-17610___
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  • P(ED1.1.00/02.0070), S, Z(MSM6198898701)
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  • 120106
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  • RIV/61988987:17610/12:A13012OM
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  • global optimization; differential evolution; adaptation; experimental comparison (en)
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  • [53E71D820540]
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  • Zakopane
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  • Berlin Heidelberg
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  • Lecture Notes in Computer Science 7269
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  • Tvrdík, Josef
  • Poláková, Radka
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  • 000314209500037
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  • Springer-Verlag
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  • 978-3-642-29352-8
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  • 17610
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