Multimodal optimization by means of evolutionary algorithms

著者

    • Preuss, Mike

書誌事項

Multimodal optimization by means of evolutionary algorithms

Mike Preuss

(Natural computing series)

Springer, c2015

大学図書館所蔵 件 / 2

この図書・雑誌をさがす

注記

Includes bibliographical references

内容説明・目次

内容説明

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.

目次

Introduction: Towards Multimodal Optimization.- Experimentation in Evolutionary Computation.- Groundwork for Niching.- Nearest-Better Clustering.- Niching Methods and Multimodal Optimization Performance.- Nearest-Better Based Niching.

「Nielsen BookData」 より

関連文献: 1件中  1-1を表示

詳細情報

  • NII書誌ID(NCID)
    BB20236066
  • ISBN
    • 9783319074061
  • LCCN
    2015956174
  • 出版国コード
    sz
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Cham
  • ページ数/冊数
    xx, 189 p.
  • 大きさ
    24 cm
  • 分類
  • 件名
  • 親書誌ID
ページトップへ