000			03836cam a2200589Mi 4500
001			9780429293030
003			FlBoTFG
005			20220711212402.0
006			m o d
007			cr |n|||||||||
008			190823s2019 flu ob 000 0 eng
040			_aOCoLC-P _beng _cOCoLC-P _erda
020			_a9780429293030 (electronic bk)
020			_a0429293038 (electronic bk)
020			_a9781000546804 _q(electronic bk. : EPUB)
020			_a1000546802 _q(electronic bk. : EPUB)
020			_a9781000541977 _q(electronic bk. : Mobipocket)
020			_a1000541975 _q(electronic bk. : Mobipocket)
020			_a9781000537147 _q(electronic bk. : PDF)
020			_a1000537145 _q(electronic bk. : PDF)
020			_z9780367260446
020			_z0367260441
035			_a(OCoLC)1114319847
035			_a(OCoLC-P)1114319847
050		4	_aTA177.4 _b.O68 2019
072		7	_aTEC _x009060 _2bisacsh
072		7	_aTEC _x020000 _2bisacsh
072		7	_aMAT _x029000 _2bisacsh
072		7	_aKJT _2bicssc
082	0	4	_a620.001/5196 _223
245	0	0	_aOptimization using evolutionary algorithms and metaheuristics : _bapplications in engineering / _cedited by Kaushik Kumar and J. Paulo Davim.
264		1	_aBoca Raton : _bTaylor & 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, _c2019.
300			_a1 online resource (pages cm.).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	0		_aScience, technology, and management series
520			_aMetaheuristic 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
588			_aOCLC-licensed vendor bibliographic record.
650		0	_aEngineering economy. _99006
650		0	_aMathematical optimization. _94112
650		0	_aGenetic algorithms. _93938
650		0	_aMetaheuristics. _94799
650		7	_aTECHNOLOGY / Engineering / Industrial _2bisacsh _910902
650		7	_aTECHNOLOGY / Manufacturing _2bisacsh _910872
650		7	_aMATHEMATICS / Probability & Statistics / General _2bisacsh _96860
700	1		_aKumar, K. _q(Kaushik), _d1968- _eeditor. _914564
700	1		_aDavim, J. Paulo, _eeditor. _914567
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429293030
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942			_cEBK
999			_c71180 _d71180