Advancements in Optimization and Nature-Inspired Computing for Solutions in Contemporary Engineering Challenges

Adrián Andrés Toncovich (Hrsg.), Carlos Enrique Torres-Aguilar (Hrsg.), Diego Rossit (Hrsg.)

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ca. 192,59

Springer Nature Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Allgemeines, Lexika

Beschreibung

This book brings together cutting-edge research, methodologies, and applications in the field of optimization and nature-inspired computing, providing a comprehensive overview of the latest advancements and their applications in addressing contemporary challenges in engineering. The book demonstrates diverse applications of mathematical modeling in various aspects of production, logistic, design, energy, materials, and other engineering areas. The book includes topics in optimization algorithms nature-inspired computing multi-objective optimization hybrid optimization techniques evolutionary algorithms swarm intelligence machine learning for optimization applications of optimization in engineering sustainable engineering solutions big data analytics for optimization metaheuristic approaches cloud computing in optimization cyber-physical systems decision support systems emerging trends in optimization.

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Schlagwörter

Combinatorics, Optimization, Mataheuristics, Engineering Problems, Nature-Inspired algorithms, Machine learning, Neural networks