Data-Driven Evolutionary Optimization

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Sprache: Englisch

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Beschreibung

Intended for researchers and practitioners alike, this book covers carefully selected yet broad topics in optimization, machine learning, and metaheuristics. Written by world-leading academic researchers who are extremely experienced in industrial applications, this self-contained book is the first of its kind that provides comprehensive background knowledge, particularly practical guidelines, and state-of-the-art techniques. New algorithms are carefully explained, further elaborated with pseudocode or flowcharts, and full working source code is made freely available.

This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms. Applications of data-driven optimization ranging from aerodynamic design, optimization of industrial processes, to deep neural architecture search are included.

Zusammenfassung

Includes a brief introduction to mathematical programming, metaheuristic algorithms, and machine learning techniques

Presents a systematic description of most recent research advances in data-driven evolutionary optimization, including surrogate-assisted single-, multi-, and many-objective optimization

Introduces various intuitive and mathematical surrogate management strategies, such as the trust region method and acquisition functions in Bayesian optimization

Provides applications of data-driven optimization to engineering design, automation of process industry, health care, and automated machine learning

Inhaltsverzeichnis

Introduction to Optimization.- Classical Optimization Algorithms.- Evolutionary and Swarm Optimization.- Introduction to Machine Learning.- Data-Driven Surrogate-Assisted Evolutionary Optimization.- Multi-Surrogate-Assisted Single-Objective Optimization.- Surrogate-Assisted Multi-Objective Evolutionary Optimization.

Details

Erscheinungsjahr:	2022
Fachbereich:	Technik allgemein
Genre:	Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Reihe:	Studies in Computational Intelligence
Inhalt:	xxv 393 S. 83 s/w Illustr. 76 farbige Illustr. 393 p. 159 illus. 76 illus. in color.
ISBN-13:	9783030746421
ISBN-10:	3030746429
Sprache:	Englisch
Ausstattung / Beilage:	Paperback
Einband:	Kartoniert / Broschiert
Autor:	Jin, Yaochu Sun, Chaoli Wang, Handing
Auflage:	1st ed. 2021
Hersteller:	Springer International Publishing Springer International Publishing AG Studies in Computational Intelligence
Maße:	235 x 155 x 23 mm
Von/Mit:	Yaochu Jin (u. a.)
Erscheinungsdatum:	30.06.2022
Gewicht:	0,633 kg

Artikel-ID: 121978599