000 02456nam a22004095i 4500
988 _aSpringer_Robotics_2020
999 _c117009
_d117009
_x1
001 117009
003 ES-MaUEC
005 20240111050200.0
006 a||||fo|||| 00| 0
007 cr nn nnnaamaa
008 190724s2020 gw | s |||| 0|eng d
020 _a9783030248352
024 7 _a10.1007/978-3-030-24835-2
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA402.5
_b2020 EB
100 1 _aMirjalili, Seyedali
_eautor
_9671160
245 1 0 _aMulti-objective optimization using artificial intelligence techniques
_cby Seyedali Mirjalili, Jin Song Dong
250 _aFirst edition
264 1 _aCham
_bSpringer International Publishing
_c2020
300 _a1 recurso en línea (XI, 58 páginas)
_b26 ilustraciones, 25 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _atext file
_bPDF
490 1 _aSpringerBriefs in Computational Intelligence
_x2625-3704
490 0 _aTechnologies and Robotics (Springer-42732)
520 3 _aThis book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
650 7 _2embne
_9145705
_aOptimización matemática
650 7 _2embne
_aInteligencia artificial
_9413115
700 1 _aDong, Jin Song
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
776 0 8 _iPrinted edition:
_z9783030248345
776 0 8 _iPrinted edition:
_z9783030248369
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-24835-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _dz
_feng
_ggw
_h0
_b01/2020
_eel
_zSI