Engineering Optimization: An Introduction with Metaheuristic Application

Engineering Optimization: An Introduction with Metaheuristic Application presents a clear and practical guide to modern optimization methods used in engineering design and decision-making. The book focuses on how metaheuristic algorithms, such as genetic algorithms, particle swarm optimization, and simulated annealing, can be applied to solve complex, real-world engineering problems. It introduces readers to key principles in optimization theory while emphasizing computational techniques that balance performance and efficiency. Designed for students, engineers, and researchers, the book provides insight into modeling objectives, defining constraints, and evaluating trade-offs in various engineering domains. Readers are introduced to a range of tools that support optimal design and problem-solving, enabling them to develop innovative solutions across disciplines such as mechanical, electrical, and civil engineering. Emphasizing both conceptual understanding and algorithmic implementation, this book is a valuable resource for mastering contemporary optimization strategies in a practical and application-oriented context.