000			03572nam a22003855i 4500
001			393983
003			ES-MaUEC
005			20230102123045.0
007			cr nn 008mamaa
008			220917s2022 sz | s |||| 0|eng d
020			_a9783031134296
024	7		_a10.1007/978-3-031-13429-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aKaveh, Ali _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aAdvanced Metaheuristic Algorithms and Their Applications in Structural Optimization _cby Ali Kaveh, Kiarash Biabani Hamedani
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (X, 362 páginas) _b160 ilustraciones, 159 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 Computational Intelligence _x1860-9503 _v1059
505	0		_aIntroduction -- Set-Theoretical Shuffled Shepherd Optimization Algorithm for Optimal Design of Reinforced Concrete Cantilever Retaining Wall Structures -- Set-Theoretical Variants of the Teaching-Learning-Based Optimization Algorithm for Structural Optimization with Frequency Constraints -- Enhanced Versions of the Shuffled Shepherd Optimization Algorithm for Structural Optimization -- Set-Theoretical Metaheuristic Algorithms for Reliability-Based Design Optimization of Truss Structures -- Optimal Analysis in the Service of Frequency-Constrained Structural Optimization with Set-Theoretical Jaya Algorithm -- Discrete Structural Optimization with Set-Theoretical Jaya Algorithm -- Enhanced Forensic-Based Investigation Algorithm -- Improved Slime Mould Algorithm -- Improved Arithmetic Optimization Algorithm.
520			_aThe main purpose of the present book is to develop a general framework for population-based metaheuristics based on some basic concepts of set theory. The idea of the framework is to divide the population of individuals into subpopulations of identical sizes. Therefore, in each iteration of the search process, different subpopulations explore the search space independently but simultaneously. The framework aims to provide a suitable balance between exploration and exploitation during the search process. A few chapters containing algorithm-specific modifications of some state-of-the-art metaheuristics are also included to further enrich the book. The present book is addressed to those scientists, engineers, and students who wish to explore the potentials of newly developed metaheuristics. The proposed metaheuristics are not only applicable to structural optimization problems but can also be used for other engineering optimization applications. The book is likely to be of interest to a wide range of engineers and students who deal with engineering optimization problems.
700	1		_aBiabani Hamedani, Kiarash _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783031134289
776	0	8	_iPrinted edition: _z9783031134302
776	0	8	_iPrinted edition: _z9783031134319
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-13429-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Robotics_2022
999			_c393983 _d393983