Modern Numerical Nonlinear Optimization

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The book provides an in-depth theoretical and computational analysis of both unconstrained and constrained optimization algorithms, highlighting recent advancements in techniques and computational linear algebra. It explores the maturity of nonlinear optimization methods, detailing their convergence properties and numerical performance. Through a clear and rigorous approach, readers gain insights into the theory behind these algorithms, enabling them to understand and prove the convergence of their own methods. Additionally, it examines various modern algorithms applied to diverse optimization problems, including large-scale real-world applications.