Numerical and Evolutionary Optimization 2020

doi:10.3390/books978-3-0365-1670-7

dc.contributor.editor	Quiroz, Marcela
dc.contributor.editor	Schütze, Oliver
dc.contributor.editor	Ruiz, Juan Gabriel
dc.contributor.editor	de la Fraga, Luis Gerardo
dc.date.accessioned	2022-01-11T13:40:49Z
dc.date.available	2022-01-11T13:40:49Z
dc.date.issued	2021
dc.identifier	ONIX_20220111_9783036516691_481
dc.identifier.uri	https://directory.doabooks.org/handle/20.500.12854/76746
dc.description.abstract	This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.
dc.language	English
dc.subject.classification	thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general	en_US
dc.subject.classification	thema EDItEUR::P Mathematics and Science	en_US
dc.subject.other	robust optimization
dc.subject.other	differential evolution
dc.subject.other	ROOT
dc.subject.other	optimization framework
dc.subject.other	drainage rehabilitation
dc.subject.other	overflooding
dc.subject.other	pipe breaking
dc.subject.other	VCO
dc.subject.other	CMOS differential pair
dc.subject.other	PVT variations
dc.subject.other	Monte Carlo analysis
dc.subject.other	multi-objective optimization
dc.subject.other	Pareto Tracer
dc.subject.other	continuation
dc.subject.other	constraint handling
dc.subject.other	surrogate modeling
dc.subject.other	multiobjective optimization
dc.subject.other	evolutionary algorithms
dc.subject.other	kriging method
dc.subject.other	ensemble method
dc.subject.other	adaptive algorithm
dc.subject.other	liquid storage tanks
dc.subject.other	base excitation
dc.subject.other	artificial intelligence
dc.subject.other	Multi-Gene Genetic Programming
dc.subject.other	computational fluid dynamics
dc.subject.other	finite volume method
dc.subject.other	JSSP
dc.subject.other	CMOSA
dc.subject.other	CMOTA
dc.subject.other	chaotic perturbation
dc.subject.other	fixed point arithmetic
dc.subject.other	FP16
dc.subject.other	pseudo random number generator
dc.subject.other	incorporation of preferences
dc.subject.other	multi-criteria classification
dc.subject.other	decision-making process
dc.subject.other	multi-objective evolutionary optimization
dc.subject.other	outranking relationships
dc.subject.other	decision maker profile
dc.subject.other	profile assessment
dc.subject.other	region of interest approximation
dc.subject.other	optimization using preferences
dc.subject.other	hybrid evolutionary approach
dc.subject.other	forecasting
dc.subject.other	Convolutional Neural Network
dc.subject.other	LSTM
dc.subject.other	COVID-19
dc.subject.other	deep learning
dc.subject.other	trust region methods
dc.subject.other	multiobjective descent
dc.subject.other	derivative-free optimization
dc.subject.other	radial basis functions
dc.subject.other	fully linear models
dc.subject.other	decision making process
dc.subject.other	cognitive tasks
dc.subject.other	recommender system
dc.subject.other	project portfolio selection problem
dc.subject.other	usability evaluation
dc.subject.other	multi-objective portfolio optimization problem
dc.subject.other	trapezoidal fuzzy numbers
dc.subject.other	density estimators
dc.subject.other	steady state algorithms
dc.subject.other	protein structure prediction
dc.subject.other	Hybrid Simulated Annealing
dc.subject.other	Template-Based Modeling
dc.subject.other	structural biology
dc.subject.other	Metropolis
dc.subject.other	optimization
dc.subject.other	linear programming
dc.subject.other	energy central
dc.title	Numerical and Evolutionary Optimization 2020
dc.type	book
oapen.identifier.doi	10.3390/books978-3-0365-1670-7
oapen.relation.isPublishedBy	46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn	9783036516691
oapen.relation.isbn	9783036516707
oapen.pages	364
oapen.place.publication	Basel, Switzerland

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