Intelligent Optimization: Principles, Algorithms and Applications

Li, Changhe, Han, Shoufei, Zeng, Sanyou

Intelligent Optimization: Principles, Algorithms and Applications
  • 出版商: Springer
  • 出版日期: 2024-07-11
  • 售價: $2,580
  • 貴賓價: 9.5 折 $2,451
  • 語言: 英文
  • 頁數: 376
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9819732859
  • ISBN-13: 9789819732852
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engaged in self-study. Serving as a significant reference, it delves into advanced topics within the evolutionary computation field, including multi-objective optimization, dynamic optimization, constrained optimization, robust optimization, expensive optimization, and other pivotal scientific studies related to optimization.

Designed to be approachable and inclusive, this textbook equips readers with the essential mathematical background necessary for understanding intelligent optimization. It employs an accessible writing style, complemented by extensive pseudo-code and diagrams that vividly illustrate the mechanisms, principles, and algorithms of optimization. With a focus on practicality, this textbook provides diverse real-world application examples spanning engineering, games, logistics, and other domains, enabling readers to confidently apply intelligent techniques to actual optimization problems.

Recognizing the importance of hands-on experience, the textbook introduces the Open-source Framework for Evolutionary Computation platform (OFEC) as a user-friendly tool. This platform serves as a comprehensive toolkit for implementing, evaluating, visualizing, and benchmarking various optimization algorithms. The book guides readers on maximizing the utility of OFEC for conducting experiments and analyses in the field of evolutionary computation, facilitating a deeper understanding of intelligent optimization through practical application.

商品描述(中文翻譯)

本教科書全面探索智能優化的基礎原理、算法和應用，是本科和研究生人工智能課程的理想資源。同樣適用於活躍的研究人員和自學者。作為一本重要的參考書，它深入探討了進化計算領域的高級主題，包括多目標優化、動態優化、約束優化、魯棒優化、昂貴優化以及與優化相關的其他重要科學研究。

本教科書旨在易於理解且包容性強，為讀者提供了理解智能優化所需的基本數學背景。它採用易於理解的寫作風格，並配有大量的偽代碼和圖表，生動地展示了優化的機制、原理和算法。本教科書著重實用性，提供了涵蓋工程、遊戲、物流和其他領域的多樣真實應用示例，使讀者能夠自信地將智能技術應用於實際優化問題。

為了重視實踐經驗的重要性，本教科書介紹了開源進化計算平台（OFEC）作為一個用戶友好的工具。該平台作為一個全面的工具包，用於實施、評估、可視化和基準測試各種優化算法。本書指導讀者如何最大限度地利用OFEC在進化計算領域進行實驗和分析，從而促進對智能優化的實際應用的更深入理解。

作者簡介

Changhe Li received the B.Sc. and M.Sc. degrees in computer science from the China University of Geosciences, Wuhan, China, in 2005 and 2008, respectively, and the Ph.D. degree in computer science from the University of Leicester, Leicester, U.K., in July 2011. He is currently a professor of School of Artificial Intelligence, Anhui University of Sciences &Technology. He is the Vice Chair of the Task Force on Evolutionary Computation in Dynamic and Uncertain Environments. His research interests are intelligent optimization and machine learning.

Shoufei Han received the B.S. degree in computer science from Hefei University, Hefei, China, in2012, the M.S. degree in computer science from Shenyang Aerospace University, Shenyang, China, in 2018, and the Ph.D. degree in computer science with the Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2022. He is an Associate Professor with the School of Artificial Intelligence, Anhui University of Sciences &Technology. His current research interests include machine learning, intelligent optimization algorithms, feature selection, data mining and evolutionary computation.

Sanyou Zeng received the M.Sc. degree in mathematics from Hunan University, Changsha, China, in 1995, and the Ph.D. degree in computer science from Wuhan University, Wuhan, China, in 2002. He has been a Professor with the China University of Geosciences, Wuhan, since 2004. His current research interests include evolutionary computation with machine learning for solving problems with constraints, multiobjective, dynamic environments, and expensive costs, especially antenna design problem.

Shengxiang Yang received the Ph.D. degree from Northeastern University, Shenyang, China, in 1999. He is currently a Professor of Computational Intelligence and the Deputy Director of the Institute of Artificial Intelligence, School of Computer Science and Informatics, De Montfort University, Leicester, U.K. He has over 380 publications with an H-index of 65 according to Google Scholar. His current research interests include evolutionary computation, swarm intelligence, artificial neural networks, data mining and data stream mining, and relevant real-world applications. Prof. Yang serves as an Associate Editor/Editorial Board Member for a number of international journals, such as the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Information Sciences, and CAAI Transactions on Intelligence Technology.

作者簡介(中文翻譯)

Changhe Li於2005年和2008年分別獲得中國地質大學的計算機科學學士和碩士學位，並於2011年7月獲得英國萊斯特大學的計算機科學博士學位。他目前是安徽科技學院人工智能學院的教授，並擔任動態和不確定環境下演化計算任務組的副主席。他的研究興趣包括智能優化和機器學習。

Shoufei Han於2012年獲得合肥學院的計算機科學學士學位，2018年獲得沈陽航空航天大學的計算機科學碩士學位，並於2022年獲得南京航空航天大學的計算機科學博士學位。他是安徽科技學院人工智能學院的副教授。他目前的研究興趣包括機器學習、智能優化算法、特徵選擇、數據挖掘和演化計算。

Sanyou Zeng於1995年獲得湖南大學的數學碩士學位，並於2002年獲得武漢大學的計算機科學博士學位。自2004年以來，他一直是中國地質大學武漢的教授。他目前的研究興趣包括利用機器學習進行具有約束條件、多目標、動態環境和高成本的問題的演化計算，尤其是天線設計問題。

Shengxiang Yang於1999年獲得中國東北大學的博士學位。他目前是英國萊斯特市德蒙福特大學計算機科學與信息學院人工智能研究所的計算智能教授和副主任。根據Google Scholar，他已發表了380多篇論文，H指數為65。他目前的研究興趣包括演化計算、群體智能、人工神經網絡、數據挖掘和數據流挖掘，以及相關的實際應用。楊教授擔任多個國際期刊的副編輯/編委會成員，例如IEEE演化計算交易、IEEE控制系統交易、信息科學和中國人工智能學會智能技術交易。

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