Nonlinear Programming

BASICS. The Nature of Optimization Problems. Analytical Background. Factorable Functions. UNCONSTRAINED PROBLEMS. Unconstrained Optimization Models. Minimizing a Function of a Single Variable. General Convergence Theory for Unconstrained Minimization Algorithms. Newton's Method With Variations. Conjugate Direction Algorithms. Quasi-Newton Methods. OPTIMALITY CONDITIONS FOR CONSTRAINED PROBLEMS. First- and Second-Order Optimality Conditions. Applications of Optimality Conditions. LINEARLY CONSTRAINED PROBLEMS. Models with Linear Constraints. Variable-Reduction Algorithms. NONLINEARLY CONSTRAINED PROBLEMS. Models with Nonlinear Constraints. Direct Algorithms for Nonlinearly Constrained Problems. Sequential Unconstrained Minimization Techniques. Sequential Constraint Linearization Techniques. OTHER TOPICS. Obtaining Global Solutions. Geometric Programming. References. Author and Subject Indexes.