000			02822 a2200409 4500
001			22775589
003			0000
005			20251017102029.0
006			m |o d |
007			cr_|||||||||||
008			220324t20232023flu of 001 0 eng
010			_a 2022014423
020			_a9781032070926
035			_a22775589
040			_aDLC _beng _cDLC _erda _dDLC
042			_apcc
050	0	0	_aQA 76.9 .N37
082	0	0	_a006.3/82 _223/eng20220901
100			_aMirjalili, Seyedali (editor)
245	0	0	_aHandbook of moth-flame optimization algorithm : _bvariants, hybrids, improvements, and applications / _cedited by Seyedali Mirjalili.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c2023.
300			_axiv, 331p. ill.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	0		_aAdvances in metaheurists
504			_aIncludes index.
520			_a"Moth-Flame Optimization algorithm is an emerging meta-heuristic and has been widely used in both science and industry. Solving optimization problem using this algorithm requires addressing a number of challenges including multiple objectives, constraints, binary decision variables, large-scale search space, dynamic objective function, noisy parameters, just to name a few. Handbook of Moth-Flame Optimization Algorithm: Variants, Hybrids, Improvements, and Applications provides an in-depth analysis of this algorithm and the existing methods in the literature to cope with such challenges. Key features: Reviews the literature of the Moth-Flame Optimization algorithm. Provides an in-depth analysis of equations, mathematical models, and mechanisms of the Moth-Flame Optimization algorithm. Proposes different variants of the Moth-Flame Optimization algorithm to solve binary, multi-objective, noisy, dynamic, and combinatorial optimization problems. Demonstrates how to design, develop, and test different hybrids of Moth-Flame Optimization algorithm. Introduces several applications areas of the Moth-Flame Optimization algorithm. This handbook will interest researchers in evolutionary computation, meta-heuristics and to those who are interested in applying Moth-Flame Optimization algorithm and swarm intelligence methods overall to different application areas"-- _cProvided by publisher.
588			_aDescription based on print version record.
650		0	_aNature-inspired algorithms.
650		0	_aArtificial intelligence.
700	1		_aMirjalili, Seyedali, _eeditor.
776	0	8	_iPrint version: _tHandbook of moth-flame optimization algorithm _bFirst edition. _dBoca Raton : CRC Press, [2023] _z9781032070919 _w(DLC) 2022014422
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBK
999			_c43875 _d43875