Multimodal Optimization by Means of Evolutionary Algorithms
暫譯: 透過演化演算法的多模態優化

Preuss, Mike

Multimodal Optimization by Means of Evolutionary Algorithms
  • 出版商: Springer
  • 出版日期: 2019-03-14
  • 售價: $4,430
  • 貴賓價: 9.5 折 $4,209
  • 語言: 英文
  • 頁數: 189
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3319791567
  • ISBN-13: 9783319791562
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

商品描述

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization.

The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used.

The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.

商品描述(中文翻譯)

本書提供了多模態優化演算法的首個全面分類法，涵蓋了如細分(niching)、平行進化演算法(parallel evolutionary algorithms)和全域優化(global optimization)等主題。

作者解釋了進化演算法中的細分及其優點；他檢視了這些演算法作為實驗分析的診斷工具的適用性，特別是在檢測問題（類型）特性方面；並且他使用不同的基準測試問題集來測量和比較細分演算法與經典進化演算法(canonical EAs)的性能。他的研究整合了該領域近期的成功案例，展示並解釋了使用案例、演算法和性能指標，始終專注於優化過程的目標以及對所使用演算法的深入理解。

本書將對計算智能領域的研究人員和實務工作者特別有用，尤其是那些從事啟發式搜尋(heuristic search)、多模態優化、進化計算(evolutionary computing)和實驗分析的專業人士。

作者簡介

Dr. Mike Preuss got his Ph.D. in the Technische Universität Dortmund and he is now a researcher at the Westfälische Wilhelms-Universität Münster. He has published in the leading journals and conferences on various aspects of computational intelligence, in particular evolutionary computing, heuristics, search and multicriteria optimization and served on many of the key academic conference committees, journal boards and review committees in this field. He is a leading figure in the application of computational and artificial intelligence to games.

作者簡介(中文翻譯)

麥克·普魯斯博士（Dr. Mike Preuss）在多特蒙德工業大學（Technische Universität Dortmund）獲得博士學位，目前是明斯特西法倫威廉姆斯大學（Westfälische Wilhelms-Universität Münster）的研究員。他在計算智能的各個方面發表了多篇論文，特別是在進化計算、啟發式演算法、搜尋和多準則優化等領域，並在該領域的許多重要學術會議委員會、期刊編輯委員會和審稿委員會中擔任職務。他是計算智能和人工智能應用於遊戲領域的領軍人物。

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