000			03547nam a22003975i 4500
001			393904
003			ES-MaUEC
005			20230102123035.0
007			cr nn 008mamaa
008			220903s2022 sz | s |||| 0|eng d
020			_a9783031075162
024	7		_a10.1007/978-3-031-07516-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aHandbook of Nature-Inspired Optimization Algorithms: The State of the Art _bVolume II: Solving Constrained Single Objective Real-Parameter Optimization Problems _cedited by Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (X, 214 páginas) _b79 ilustraciones, 51 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Systems Decision and Control _x2198-4190 _v213
505	0		_aParticle swarm optimization based optimization for in-dustry inspection -- Ant Algorithms: from Drawback Identification to Quality and Speed Improvement -- Fault location techniques based on traveling waves with application in the protection of distribution systems with renewable energy and particle swarm optimization -- Improved Particle Swarm Optimization and Non-Quadratic Penalty Method for Non-Linear Programming Problems with Equality Constraints -- Recent Trends in Face Recognition Using Metaheuristic Optimization.
520			_aThis book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs). The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.
700	1		_aMohamed, Ali Wagdy _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aOliva, Diego _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSuganthan, Ponnuthurai Nagaratnam _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783031075155
776	0	8	_iPrinted edition: _z9783031075179
776	0	8	_iPrinted edition: _z9783031075186
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-07516-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Robotics_2022
999			_c393904 _d393904