evolution strategy


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evolution strategy

(ES) A kind of evolutionary algorithm where individuals (potential solutions) are encoded by a set of real-valued "object variables" (the individual's "genome"). For each object variable an individual also has a "strategy variable" which determines the degree of mutation to be applied to the corresponding object variable. The strategy variables also mutate, allowing the rate of mutation of the object variables to vary.

An ES is characterised by the population size, the number of offspring produced in each generation and whether the new population is selected from parents and offspring or only from the offspring.

ES were invented in 1963 by Ingo Rechenberg, Hans-Paul Schwefel at the Technical University of Berlin (TUB) while searching for the optimal shapes of bodies in a flow.
References in periodicals archive ?
As a network evolution strategy consultant, Huawei will assist Mobily with its 4.5G to 5G evolution, and its target network planning (including spectrum and user experience).
"This is one of several strategic investments that build upon Shuaa's evolution strategy, and helps take the region's financial services landscape to a new level.
The algorithm is mainly improved in two aspects: evolution strategy and weight vector.
The evolution strategy employed was es ([mu] + [lambda]), where a set of [mu] parents are used to create a [lambda] offspring in each generation.
Selected methods are: Random Search, Downhill Simplex, Hill Climbing, Tabu Search, Local Search, Simulated Annealing [5], Evolution Strategy [6], Differential Evolution [7].
Lv, "Improved differential evolution strategy for antenna array pattern synthesis problems," Progress In Electromagnetics Research, Vol.
[19.] Qing, A., "Dynamic differential evolution strategy and applications in electromagnetic inverse scattering problems," IEEE Trans.
The update is coming as a part of a common software evolution strategy oriented toward mixed OS network backup management, also bringing remote Linux image backup and a bunch of other smart options.
This evolution strategy allows the bacteria to maximise their chances of making it to the next generation.
Nie, "The application of a modified differential evolution strategy to some array pattern synthesis problems", IEEE Trans.
Therefore, this paper focuses on a newly developed EA based on the paradigm of evolution strategy.
A combination of the evolution strategy and Levenberg-Marquardt method was developed [8].

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