Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Name: Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization
Brand: IntechOpen
SKU: 9781789233285
Price: 627.3 RON
Availability: InStock

Autor: Javier Del Ser Lorente, Eneko Osaba

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Legare: Copertă tare

Editura: IntechOpen

Disponibilitate: În depozitul extern

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

Informații despre carte

Autor

Javier Del Ser Lorente, Eneko Osaba

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2018

Pagini

EAN

9781789233285

ISBN

1789233283

Enbook ID

23923653

Editura

IntechOpen

Greutate

376

Dimensiuni

180 x 260 x 10

Descriere completă

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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