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Autore: | Lara Adriana |
Titolo: | Numerical and Evolutionary Optimization |
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 |
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 |
Opac: | Controlla la disponibilità qui |