Data-Driven Global Optimization Methods and Applications. Huachao Dong, Peng Wang, Jinglu Li
Data-Driven-Global.pdf
ISBN: 9781041065753 | 348 pages | 9 Mb
- Data-Driven Global Optimization Methods and Applications
- Huachao Dong, Peng Wang, Jinglu Li
- Page: 348
- Format: pdf, ePub, fb2, mobi
- ISBN: 9781041065753
- Publisher: CRC Press
Free audiobook download for ipod touch Data-Driven Global Optimization Methods and Applications
This book presents recent advances in data-driven global optimization methods, combining theoretical foundations with real-world applications to address complex engineering optimization challenges. The book begins with an overview of the state of the art, key technologies and standard benchmark problems in the field. It then delves into several innovative approaches: space reduction-based, hybrid surrogate model-based and multi-surrogate model-based global optimization, followed by surrogate-assisted constrained global optimization, discrete global optimization and high-dimensional global optimization. These methods represent a variety of optimization techniques that excel in both optimization capability and efficiency, making them ideal choices for complex engineering optimization problems. Through benchmark test problems and real-world engineering applications, the book illustrates the practical implementation of these methods, linking established theories with cutting-edge research in industrial and engineering optimization. Both a professional book and an academic reference, this title will provide valuable insights for researchers, students, engineers and practitioners in a variety of fields, including optimization methods and algorithms, engineering design and manufacturing and artificial intelligence and machine learning.
Data-Driven Global Optimization Methods and Applications
Data-Driven Global Optimization Methods and Applications. Author: Huachao Dong , Peng Wang , Jinglu Li Publisher: Taylor & Francis Ltd
Global Optimization: Theory, Algorithms, and Applications
This volume contains a thorough overview of the rapidly growing field of global optimization, with chapters on key topics such as. complexity,.
Data-Driven Global Optimization Methods And Applications eBook
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Journal of Global Optimization
The Journal of Global Optimization publishes carefully refereed papers that encompass theoretical, computational, and applied aspects of global optimization.
On Data-Driven Optimization Methods in the Design and Control of .
PDF | In various applications in engineering, science, and other domains, we are faced with various difficult optimization problems, entailing the.
Parametric :: Publications - Texas A&M University
AI-Based Predictive Analytics for Enhancing Data-Driven Supply Chain Optimization. Journal of Global Optimization 2025, Accepted. Montano Flores, B. S. M.; De .
A Review of Intelligent Airfoil Aerodynamic Optimization Methods .
Finally, the application of data-driven advanced models in aerodynamic design is summarized, and an outlook for future research is presented. Mathematics 12 .
Data-Driven Strategies for Optimization of Chemical Processes
Data-Driven Strategies for Optimization of Chemical Processes: Algorithms and Applications . novel global-search and local-search DFO algorithms. We provide the .
Global Optimization Methods in Geophysical Inversion
This Book has been cited by the following publications. This list is generated based on data provided by Crossref. Barros, Tiago Ferrari, Rafael Krummenauer .
Optimization of Complex Systems: Theory, Models, Algorithms and .
This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July .
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Motivated by this growing availability, we propose a novel schema for utilizing data to design uncertainty sets for robust optimization using sta- tistical .
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The global aim of RATIONAL is to model and solve realistic . data-driven thinking, machine learning, and robust optimization methods. It .
Data-Driven Global Optimization Methods and Applications
The presented text deals with design of the modification of the low-profile dipole planar inverted cone antenna (LPdiPICA), which is originally .
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