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This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.
This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences.
Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics
This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from divers
Optimization is a rich and thriving mathematical discipline, and the underlying theory of current computational optimization techniques grows ever more sophisti
This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the la
