Advances in Evolutionary Algorithms Research

Name: Advances in Evolutionary Algorithms Research
Brand: Nova Science Publishers Inc
SKU: 9781634638494
Price: 261.93 EUR
Availability: InStock

The State of the Class

Автор: Jacek Tittenbrun

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Корици: С твърди корици

Издател: Nova Science Publishers Inc

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The field of evolutionary algorithms produces various theoretical approaches that help search for gl...

Информация за книгата

Автор

Jacek Tittenbrun

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2015

страници

117

EAN

9781634638494

ISBN

9781634638494

Enbook ID

03198359

Издател

Nova Science Publishers Inc

Теглоt

474

Размери

264 x 214 x 15

Пълно описание

The field of evolutionary algorithms produces various theoretical approaches that help search for global optima within complex environments. These environments are often highly multidimensional, non-linear, noisy, and with many constraints. Not only one, but frequently several, even conflicting, objectives need to be met while searching for the optimal solutions. This book presents advances in the research and applications of evolutionary algorithms. There is a rich history of theoretical research and practical solutions in this field. Namely, evolutionary algorithms, with their intrinsic parallelism, have proved to be successful in a variety of problem domains in science, engineering and business. According to the no-free lunch theorem for optimisation no super algorithm exists for all optimisation problems. Therefore, the advances in this research field are also devoted to the identification of combination of problem classes and effective optimisation methods, as well as the innovative and hybrid implementations of the algorithms. This book consists of seven chapters covering the survey and theory on multimodal, multi-memetic and multi-objective properties and algorithm performance. Furthermore, the algorithms are applied to real-world mechanical, biological, and chemical problems, as well as to theoretical benchmarks.

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Advances in Evolutionary Algorithms Research

The State of the Class

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