Name: Extremal Optimization: Fundamentals, Algorithms, and Applications (en Inglés)
SKU: 53496110
Price: 59.58 USD
Availability: InStock
Author: Yong-Zai Lu; Yu-Wang Chen; Min-Rong Chen; Peng Chen; Guo-Qiang Zeng
ISBN: 9780367658588

portada Extremal Optimization: Fundamentals, Algorithms, and Applications (en Inglés)

Extremal Optimization: Fundamentals, Algorithms, and Applications (en Inglés)

Formato

Libro Físico

Editorial

Auerbach Publications

Autor

Yong-Zai Lu; Yu-Wang Chen; Min-Rong Chen; Peng Chen; Guo-Qiang Zeng

Año

2020

Idioma

Inglés

N° páginas

350

Encuadernación

Tapa Blanda

ISBN13

9780367658588

N° edición

Categorías

Minería de datos («data mining»)

Extremal Optimization: Fundamentals, Algorithms, and Applications (en Inglés)

Yong-Zai Lu; Yu-Wang Chen; Min-Rong Chen; Peng Chen; Guo-Qiang Zeng (Autor) · Auerbach Publications · Tapa Blanda

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Reseña del libro "Extremal Optimization: Fundamentals, Algorithms, and Applications (en Inglés)"

Extremal Optimization: Fundamentals, Algorithms, and Applications introduces state-of-the-art extremal optimization (EO) and modified EO (MEO) solutions from fundamentals, methodologies, and algorithms to applications based on numerous classic publications and the authors’ recent original research results. It promotes the movement of EO from academic study to practical applications. The book covers four aspects, beginning with a general review of real-world optimization problems and popular solutions with a focus on computational complexity, such as "NP-hard" and the "phase transitions" occurring on the search landscape.Next, it introduces computational extremal dynamics and its applications in EO from principles, mechanisms, and algorithms to the experiments on some benchmark problems such as TSP, spin glass, Max-SAT (maximum satisfiability), and graph partition. It then presents studies on the fundamental features of search dynamics and mechanisms in EO with a focus on self-organized optimization, evolutionary probability distribution, and structure features (e.g., backbones), which are based on the authors’ recent research results. Finally, it discusses applications of EO and MEO in multiobjective optimization, systems modeling, intelligent control, and production scheduling.The authors present the advanced features of EO in solving NP-hard problems through problem formulation, algorithms, and simulation studies on popular benchmarks and industrial applications. They also focus on the development of MEO and its applications. This book can be used as a reference for graduate students, research developers, and practical engineers who work on developing optimization solutions for those complex systems with hardness that cannot be solved with mathematical optimization or other computational intelligence, such as evolutionary computations.