Modern Numerical Nonlinear Optimization
- 844 pages
- 30 hours of reading
The book offers an in-depth theoretical and computational exploration of both unconstrained and constrained optimization algorithms, highlighting the integration of advanced computational linear algebra techniques. It provides a rigorous yet accessible discussion on the convergence properties of nonlinear optimization methods, equipping readers with the knowledge to validate their own algorithms. Additionally, it examines the performance of various modern algorithms across diverse test problems and real-world applications, making it a valuable resource for understanding complex optimization challenges.
