Titlebook: Classical and Evolutionary Algorithms in the Optimization of Optical Systems; Darko Vasiljevi? Book 2002 Kluwer Academic Publishers 2002 e

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Evolution Strategies,Evolution strategies (ES) are algorithms which imitate the principles of natural selection as a method to solve parameter optimization problems. Bienert, Rechenberg and Schwefel developed them in Germany during the 1960s. The evolution strategies can be divided in two large groups:

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Multimembered evolution strategies ES GRUP and ES REKO implementation, one genetic operator — the mutation. The multimembered evolution strategies represent a more complex model of the evolution simulation. In this chapter the implementation of two variants of the multimembered evolution strategies is described:

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,Synopsis—An Integrated Analysis,ulation of genetic processes. Over many generations natural populations evolve according to the principles of natural selection and “survival of the fittest” first described by Charles Darwin in a famous book . [25]. By mimicking this process, genetic algorithms are able to “develop — evolve” soluti

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