This updated textbook offers an overview of convex analysis, the foundations of optimization and computational methods. It emphasizes the implementation of numerical methods and focuses on the concept of error and the need to analyze and predict it.
CONVEX ANALYSIS; Convex Sets; Convex Functions and Generalizations; OPTIMALITY CONDITIONS AND DUALITY; The Fritz John and the Karush-Kuhn-Tucker Optimality Conditions; Constraint Qualifications; Lagrangian Duality and Saddle Point Optimality Conditions; ALGORITHMS AND THEIR CONVERGENCE; The Concept of an Algorithm; Unconstrained Optimization; Penalty and Barrier Functions; Methods of Feasible Directions; Linear Complementary Problem, and Quadratic, Separable, Fractional, and Geometric Programming; Appendices; Bibliography; Index.
Non-linear Programming: Theory and Algorithms by M. S. Bazaraa
M. S. Bazaraa
Used - Very Good
John Wiley and Sons Ltd
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