Advances in Metaheuristics Algorithms: Methods and Applications (Record no. 77134)

000 -LEADER
fixed length control field 03733nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-319-89309-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801215124.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180410s2018 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319893099
-- 978-3-319-89309-9
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Cuevas, Erik.
245 10 - TITLE STATEMENT
Title Advances in Metaheuristics Algorithms: Methods and Applications
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIV, 218 p. 48 illus., 13 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- The metaheuristic algorithm of the social-spider -- Calibration of Fractional Fuzzy Controllers by using the Social-spider method -- The metaheuristic algorithm of the Locust-search -- Identification of fractional chaotic systems by using the Locust Search Algorithm -- The States of Matter Search (SMS) -- Multimodal States of Matter search -- Metaheuristic algorithms based on Fuzzy Logic.
520 ## - SUMMARY, ETC.
Summary, etc This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.
700 1# - AUTHOR 2
Author 2 Zaldívar, Daniel.
700 1# - AUTHOR 2
Author 2 Pérez-Cisneros, Marco.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-89309-9
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Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2018.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
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-- 1860-9503 ;
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