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portada Advancements in Optimization and Nature-Inspired Computing for Solutions in Contemporary Engineering Challenges
Type
Physical Book
Collection
Springer Tracts in Nature-Inspired Computing
Year
2025
Pages
312
Format
Hardcover
Dimensions
23.5x15.5 cm
ISBN13
9789819607051

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

Adrian Andres Toncovich;Diego Rossit;Carlos Enrique Torres-Aguilar (Author) · Springer Nature Switzerland AG · Hardcover

Advancements in Optimization and Nature-Inspired Computing for Solutions in Contemporary Engineering Challenges - Adrian Andres Toncovich;Diego Rossit;Carlos Enrique Torres-Aguilar

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

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.

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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