Optimization using evolutionary algorithms and metaheuristics : (Record no. 71180)

000 -LEADER
fixed length control field 03836cam a2200589Mi 4500
001 - CONTROL NUMBER
control field 9780429293030
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711212402.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190823s2019 flu ob 000 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9780429293030 (electronic bk)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 0429293038 (electronic bk)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000546804
-- (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000546802
-- (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000541977
-- (electronic bk. : Mobipocket)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000541975
-- (electronic bk. : Mobipocket)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781000537147
-- (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1000537145
-- (electronic bk. : PDF)
082 04 - CLASSIFICATION NUMBER
Call Number 620.001/5196
245 00 - TITLE STATEMENT
Title Optimization using evolutionary algorithms and metaheuristics :
Sub Title applications in engineering /
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (pages cm.).
490 0# - SERIES STATEMENT
Series statement Science, technology, and management series
520 ## - SUMMARY, ETC.
Summary, etc Metaheuristic optimization is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem, especially with incomplete or imperfect information or limited computation capacity. This is usually applied when two or more objectives are to be optimized simultaneously. This book is presented with two major objectives. Firstly, it features chapters by eminent researchers in the field providing the readers about the current status of the subject. Secondly, algorithm-based optimization or advanced optimization techniques, which are applied to mostly non-engineering problems, are applied to engineering problems. This book will also serve as an aid to both research and industry. Usage of these methodologies would enable the improvement in engineering and manufacturing technology and support an organization in this era of low product life cycle. Features: Covers the application of recent and new algorithms Focuses on the development aspects such as including surrogate modeling, parallelization, game theory, and hybridization Presents the advances of engineering applications for both single-objective and multi-objective optimization problems Offers recent developments from a variety of engineering fields Discusses Optimization using Evolutionary Algorithms and Metaheuristics applications in engineering
700 1# - AUTHOR 2
Author 2 Kumar, K.
700 1# - AUTHOR 2
Author 2 Davim, J. Paulo,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.taylorfrancis.com/books/9780429293030
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Boca Raton :
-- Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc,
-- 2019.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering economy.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical optimization.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Genetic algorithms.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Metaheuristics.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- TECHNOLOGY / Engineering / Industrial
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- TECHNOLOGY / Manufacturing
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- MATHEMATICS / Probability & Statistics / General

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