Data-Driven Global Optimization Methods and Applications
暫譯: 數據驅動的全球優化方法與應用
Dong, Huachao, Wang, Peng, Li, Jinglu
- 出版商: CRC
- 出版日期: 2025-07-15
- 售價: $4,430
- 貴賓價: 9.5 折 $4,209
- 語言: 英文
- 頁數: 324
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1041065752
- ISBN-13: 9781041065753
尚未上市，無法訂購
相關主題
商品描述
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.
商品描述(中文翻譯)
本書介紹了數據驅動的全球優化方法的最新進展，結合理論基礎與實際應用，以應對複雜的工程優化挑戰。
本書首先概述了該領域的最新技術、關鍵技術和標準基準問題。接著深入探討幾種創新方法：基於空間縮減的全球優化、混合代理模型的全球優化以及多代理模型的全球優化，隨後是代理輔助的約束全球優化、離散全球優化和高維全球優化。這些方法代表了多種優化技術，在優化能力和效率上均表現出色，使其成為解決複雜工程優化問題的理想選擇。通過基準測試問題和實際工程應用，本書展示了這些方法的實際實施，將既有理論與工業和工程優化的前沿研究相連結。
作為一本專業書籍和學術參考資料，本書將為研究人員、學生、工程師和各領域的實務工作者提供寶貴的見解，包括優化方法和算法、工程設計與製造，以及人工智慧和機器學習。
作者簡介
Huachao Dong is Associate Professor at the School of Marine Science and Technology at Northwestern Polytechnical University, China. His research includes underwater vehicle design, digital design, multidisciplinary optimization, digital twins for underwater vehicles and data-driven global optimization, with over 50 peer-reviewed papers and 1 book published.
Peng Wang is Professor at the School of Marine Science and Technology at Northwestern Polytechnical University, China. His research focuses on surrogate-based design optimization, multidisciplinary design optimization, multicriteria decision-making and the design of underwater vehicles, with over 150 peer-reviewed papers and 6 books published.
Jinglu Li is an assistant researcher at Harbin Engineering University, China. His research includes underwater vehicle design, multidisciplinary optimization, digital twins and data-driven global optimization and he has published over 20 peer-reviewed papers.
作者簡介(中文翻譯)
董華超是中國西北工業大學海洋科學與技術學院的副教授。他的研究包括水下載具設計、數位設計、多學科優化、水下載具的數位雙胞胎以及數據驅動的全球優化，已發表超過50篇同行評審論文和1本書籍。
王鵬是中國西北工業大學海洋科學與技術學院的教授。他的研究專注於基於代理的設計優化、多學科設計優化、多準則決策以及水下載具的設計，已發表超過150篇同行評審論文和6本書籍。
李京璐是中國哈爾濱工程大學的助理研究員。他的研究包括水下載具設計、多學科優化、數位雙胞胎和數據驅動的全球優化，已發表超過20篇同行評審論文。
