| 书目名称 | Introduction to Evolutionary Algorithms | | 编辑 | Xinjie Yu,Mitsuo Gen | | 视频video | | | 概述 | Establishes background to evolutionary algorithms.Introduces students to cutting-edge evolutionary algorithms.Enables readers to advance their own research by simulating the application provided in th | | 丛书名称 | Decision Engineering | | 图书封面 |  | | 描述 | Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as:• genetic algorithms,• differential evolution,• swarm intelligence, and• artificial immune systems.The reader is introduced to a range of applications, as Introduction to Evolutionary Algorithms demonstrates how to model real world problems, how to encode and decode individuals, and how to design effective search operators according to the chromosome structures with examples of constraint optimization, multiobjective optimization, combinatorial optimization, and supervised/unsupervised learning. This emphasis on practical applications will benefit all students, whether they choose to continue their academic career or to enter a particular industry.Introduction to Evolutionary Algorithms is intended as a textbook or self-study material for both advanced undergraduates and graduate students. Additional features such | | 出版日期 | Book 2010 | | 关键词 | algorithms; artificial life; combinatorial optimization; evolution; evolutionary algorithm; genetic algor | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-84996-129-5 | | isbn_softcover | 978-1-4471-2569-3 | | isbn_ebook | 978-1-84996-129-5Series ISSN 1619-5736 Series E-ISSN 2197-6589 | | issn_series | 1619-5736 | | copyright | Springer-Verlag London 2010 |
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发表于 2025-3-21 17:46:37
