Numerical and Evolutionary Optimization

• Autore: Lara Adriana
• 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