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Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, 2013
Differential Evolution (DE) is one of the most powerful stochastic real-parameter optimization algorithms of current interest. DE operates through similar computational steps as employed by a standard Evolutionary Algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled ...
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Differential Evolution (DE) is one of the most powerful stochastic real-parameter optimization algorithms of current interest. DE operates through similar computational steps as employed by a standard Evolutionary Algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled ...
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Asynchronous Differential Evolution
2012Differential Evolution (DE) is an algorithm to solve possibly nonlinear and non-differentiable global optimization problems. Classical Differential Evolution (CDE) employs a synchronous generation-based evolution strategy. We propose a modification of the CDE algorithm by incorporating mutation, crossover and selection operations into an asynchronous ...
Evgeniya Zhabitskaya, Mikhail Zhabitsky
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A Parallel Differential Evolution Algorithm A Parallel Differential Evolution Algorithm
International Symposium on Parallel Computing in Electrical Engineering (PARELEC'06), 2006In the paper the problem of using a differential evolution algorithm for feed-forward neural network training is considered. A new parallelization scheme for the computation of the fitness function is proposed. This scheme is based on data decomposition.
Wojciech Kwedlo, Krzysztof Bandurski
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Comparing black-box differential evolution and classic differential evolution
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018Recently, black-box differential evolution (BBDE) has been proposed to overcome the search biases and sensitivity to rotation of the classic differential evolution (DE). To date, BBDE has been studied only for the 'rand' strategy and even for this strategy, no systematic experimental study has been published yet.
Aljosa Vodopija +2 more
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Polyploidy in differentiation and evolution
The International Journal of Cell Cloning, 1990Somatic and generative (germ-line) polyploidy are more widely spread phenomena among living organisms than generally thought. The occurrence of polyploidization and related events in normal and pathological differentiation, their recognized main functions, as well as the structural specificities of polyploid nuclei are reviewed, and the relationship ...
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Differential Evolution and Chaotic Series
2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP), 2018This research deals with the modern and popular hybridization of chaotic dynamics and evolutionary computation. It is aimed at the influence of chaotic sequences on the performance of four selected Differential Evolution (DE) variants. The variants of interest were: original DE/Rand/1/ and DE/Best/1/ mutation schemes, simple parameter adaptive jDE, and
Roman Senkerik +4 more
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Differential Evolution: An Overview
2016Differential evolution (DE) is one of the most influential optimization algorithms up-to-date. DE works through analogous computational steps as used by a standard evolutionary algorithm. Nevertheless, not like traditional Evolutionary Algorithms, the DE-variants agitate the current generation populace members with the scaled differences of ...
Amritpal Singh, Sushil Kumar 0005
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Multiobjective Differential Evolution and Differential Evolution for Irrigation Planning
World Environmental and Water Resources Congress 2009, 2009The present paper discusses the applicability of Multiobjective Differential Evolution (MODE) and single objective Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analyzed in the multiobjective framework using MODE.
Piyush Gupta +2 more
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Parameter Selection of Differential Evolution by another Differential Evolution Algorithm
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019The performance of differential evolution (DE) highly depends on its control parameters, especially for the first proposed simple or standard DE. Control parameters suitable for one objective function are generally not beneficial to another. To automatically find out optimal control parameter settings for different objective functions, we propose a ...
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Is Algebraic Differential Evolution Really a Differential Evolution Scheme?
2021 IEEE Congress on Evolutionary Computation (CEC), 2021The Algebraic Differential Evolution (ADE) is a recently proposed combinatorial evolutionary scheme which mimics the behaviour of the classical Differential Evolution (DE) in discrete search spaces which can be represented as finitely generated groups. ADE has been successfully applied to both permutation and binary optimization problems.
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