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

Book Details

Format Hardback or Cased Book
ISBN-10 9819607051
ISBN-13 9789819607051
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Feb 20th, 2025
Print length 312 Pages
Ksh 28,800.00
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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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