000			03074nam a22003735i 4500
001			393978
003			ES-MaUEC
005			20230102123045.0
007			cr nn 008mamaa
008			220916s2022 sz | s |||| 0|eng d
020			_a9783031068393
024	7		_a10.1007/978-3-031-06839-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aRecent Advances in Computational Optimization _bResults of the Workshop on Computational Optimization WCO 2021 _cedited by Stefka Fidanova
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (X, 388 páginas) _b62 ilustraciones, 39 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 _v1044
505	0		_aLearning to Optimize -- Optimal seating assignment in the COVID-19 era via Quantum Computing -- Hybrid Ant Colony Optimization Algorithms - Behaviour Investigation Based on Intuitionistic Fuzzy Logic -- Scheduling algorithms for single machine problem with release and delivery times -- Key Performance Indicators to Improve e-Mail Service Quality through ITIL Framework -- Contemporary Bioprocesses Control Algorithms for Educational Purposes -- Monitoring a Fleet of Autonomous Vehicles through A* like Algorithms and Reinforcement Learning -- Rather "good in, good out" than "garbage in, garbage out": A comparison of various discrete subsampling algorithms using COVID-19 data without a response variable.
520			_aThis book presents recent advances in computational optimization. The book includes important real problems like modeling of physical processes, parameter settings for controlling different processes, transportation problems, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential and integral equations which describe real processes, solving engineering and financial problems. It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming Monte Carlo method and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.
700	1		_aFidanova, Stefka _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783031068386
776	0	8	_iPrinted edition: _z9783031068409
776	0	8	_iPrinted edition: _z9783031068416
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-06839-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Robotics_2022
999			_c393978 _d393978