Multimodal Optimization by Means of Evolutionary Algorithms (Record no. 56269)

000 -LEADER
fixed length control field 02884nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-3-319-07407-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421111853.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151127s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319074078
-- 978-3-319-07407-8
082 04 - CLASSIFICATION NUMBER
Call Number 005.1
100 1# - AUTHOR NAME
Author Preuss, Mike.
245 10 - TITLE STATEMENT
Title Multimodal Optimization by Means of Evolutionary Algorithms
300 ## - PHYSICAL DESCRIPTION
Number of Pages XX, 189 p. 42 illus., 5 illus. in color.
490 1# - SERIES STATEMENT
Series statement Natural Computing Series,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction: Towards Multimodal Optimization -- Experimentation in Evolutionary Computation -- Groundwork for Niching -- Nearest-Better Clustering -- Niching Methods and Multimodal Optimization Performance -- Nearest-Better Based Niching.
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-07407-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Algorithms.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical optimization.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Algorithm Analysis and Problem Complexity.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Optimization.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1619-7127
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-- ZDB-2-SCS

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