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Numerical and Evolutionary Optimization



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Autore: Lara Adriana Visualizza persona
Titolo: Numerical and Evolutionary Optimization Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica: 1 electronic resource (230 p.)
Soggetto non controllato: model predictive control
bulbous bow
improvement differential evolution algorithm
evolutionary multi-objective optimization
location routing problem
flexible job shop scheduling problem
basic differential evolution algorithm
metric measure spaces
NEAT
genetic algorithm
multiobjective optimization
improved differential evolution algorithm
performance indicator
rubber
averaged Hausdorff distance
mixture experiments
U-shaped assembly line balancing
Genetic Programming
Local Search
driving events
surrogate-based optimization
single component constraints
crop planning
Pareto front
numerical simulations
shape morphing
genetic programming
economic crops
local search and jump search
model order reduction
optimal solutions
EvoSpace
risky driving
intelligent transportation systems
optimal control
IV-optimality criterion
Bloat
decision space diversity
modify differential evolution algorithm
power means
driving scoring functions
open-source framework
evolutionary computation
differential evolution algorithm
vehicle routing problem
multi-objective optimization
Persona (resp. second.): QuirozMarcela
SchützeOliver
Mezura-MontesEfrén
Sommario/riassunto: This book was established after the 6th 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.
Titolo autorizzato: Numerical and Evolutionary Optimization  Visualizza cluster
ISBN: 3-03921-817-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910367744103321
Lo trovi qui: Univ. Federico II
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