Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Name: Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization
Brand: IntechOpen
SKU: 9781789233285
Price: 2142 CZK
Availability: InStock

Autor: Javier Del Ser Lorente, Eneko Osaba

Jazyk:

Vazba: Pevná

Vydavatel: IntechOpen

Dostupnost: Skladem u dodavatele

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2 142 Kč

Nature-inspired algorithms have a great popularity in the current scientific community, being the fo...

Informace o knize

Autor

Javier Del Ser Lorente, Eneko Osaba

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2018

Stránek

EAN

9781789233285

ISBN

1789233283

Enbook ID

23923653

Vydavatel

IntechOpen

Hmotnost

376

Rozměry

180 x 260 x 10

Kompletní popis

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.

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Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

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