Multi-Objective Design of Antennas Using Surrogate Models

Nonfiction, Computers, Programming, Systems Analysis, Advanced Computing, Data Modeling & Design
Cover of the book Multi-Objective Design of Antennas Using Surrogate Models by Slawomir Koziel, Adrian Bekasiewicz, World Scientific Publishing Company
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Author: Slawomir Koziel, Adrian Bekasiewicz ISBN: 9781786341495
Publisher: World Scientific Publishing Company Publication: November 18, 2016
Imprint: WSPC (EUROPE) Language: English
Author: Slawomir Koziel, Adrian Bekasiewicz
ISBN: 9781786341495
Publisher: World Scientific Publishing Company
Publication: November 18, 2016
Imprint: WSPC (EUROPE)
Language: English

This book addresses computationally-efficient multi-objective optimization of antenna structures using variable-fidelity electromagnetic simulations, surrogate modeling techniques, and design space reduction methods. Based on contemporary research, it formulates multi-objective design tasks, highlights related challenges in the context of antenna design, and discusses solution approaches. Specific focus is on providing methodologies for handling computationally expensive simulation models of antenna structures in the sense of their multi-objective optimization. Also given is a summary of recent developments in antenna design optimization using variable-fidelity simulation models. Numerous examples of real-world antenna design problems are provided along with discussions and recommendations for the readers interested in applying the considered methods in their design work.

Written with researchers and students in mind, topics covered can also be applied across a broad spectrum of aeronautical, mechanical, electrical, biomedical and civil engineering. It is of particular interest to those dealing with optimization, computationally expensive design tasks and simulation-driven design.

Contents:

  • Introduction
  • Simulation-Driven Antenna Design
  • Introduction to Numerical Optimization
  • Global Optimization Using Population-Based Metaheuristics
  • Surrogate-Based Modeling and Optimization
  • Multi-Objective Optimization
  • Multi-Objective Antenna Optimization Using Surrogate Models
  • Design Space Reduction Methods
  • Multi-Objective Optimization of Antenna Structures. Application Case Studies
  • Selected Topics and Practical Issues
  • Applications in Other Engineering Disciplines
  • Applications of Multi-Objective Optimization
  • Discussion and Recommendations

Readership: Researchers and students of aeronautical, mechanical, electrical, biomedical and civil engineering; those dealing with optimization, computationally expensive design tasks and simulation-driven design.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book addresses computationally-efficient multi-objective optimization of antenna structures using variable-fidelity electromagnetic simulations, surrogate modeling techniques, and design space reduction methods. Based on contemporary research, it formulates multi-objective design tasks, highlights related challenges in the context of antenna design, and discusses solution approaches. Specific focus is on providing methodologies for handling computationally expensive simulation models of antenna structures in the sense of their multi-objective optimization. Also given is a summary of recent developments in antenna design optimization using variable-fidelity simulation models. Numerous examples of real-world antenna design problems are provided along with discussions and recommendations for the readers interested in applying the considered methods in their design work.

Written with researchers and students in mind, topics covered can also be applied across a broad spectrum of aeronautical, mechanical, electrical, biomedical and civil engineering. It is of particular interest to those dealing with optimization, computationally expensive design tasks and simulation-driven design.

Contents:

Readership: Researchers and students of aeronautical, mechanical, electrical, biomedical and civil engineering; those dealing with optimization, computationally expensive design tasks and simulation-driven design.

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