Nonlinear Programming: Theory, Algorithms and Applications

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