04812nam 2201273z- 450 991055763100332120231214133406.0(CKB)5400000000045104(oapen)https://directory.doabooks.org/handle/20.500.12854/76746(EXLCZ)99540000000004510420202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierNumerical and Evolutionary Optimization 2020Basel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (364 p.)3-0365-1669-7 3-0365-1670-0 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.Research & information: generalbicsscMathematics & sciencebicsscrobust optimizationdifferential evolutionROOToptimization frameworkdrainage rehabilitationoverfloodingpipe breakingVCOCMOS differential pairPVT variationsMonte Carlo analysismulti-objective optimizationPareto Tracercontinuationconstraint handlingsurrogate modelingmultiobjective optimizationevolutionary algorithmskriging methodensemble methodadaptive algorithmliquid storage tanksbase excitationartificial intelligenceMulti-Gene Genetic Programmingcomputational fluid dynamicsfinite volume methodJSSPCMOSACMOTAchaotic perturbationfixed point arithmeticFP16pseudo random number generatorincorporation of preferencesmulti-criteria classificationdecision-making processmulti-objective evolutionary optimizationoutranking relationshipsdecision maker profileprofile assessmentregion of interest approximationoptimization using preferenceshybrid evolutionary approachforecastingConvolutional Neural NetworkLSTMCOVID-19deep learningtrust region methodsmultiobjective descentderivative-free optimizationradial basis functionsfully linear modelsdecision making processcognitive tasksrecommender systemproject portfolio selection problemusability evaluationmulti-objective portfolio optimization problemtrapezoidal fuzzy numbersdensity estimatorssteady state algorithmsprotein structure predictionHybrid Simulated AnnealingTemplate-Based Modelingstructural biologyMetropolisoptimizationlinear programmingenergy centralResearch & information: generalMathematics & scienceQuiroz Marcelaedt1277553Schütze OliveredtRuiz Juan Gabrieledtde la Fraga Luis GerardoedtQuiroz MarcelaothSchütze OliverothRuiz Juan Gabrielothde la Fraga Luis GerardoothBOOK9910557631003321Numerical and Evolutionary Optimization 20203011628UNINA