Nonlinear Programming: Concepts, Algorithms and Applications
Nonlinear Programming: Concepts, Algorithms and ApplicationsL. T. BieglerChemical Engineering DepartmentCarnegie Mellon UniversityPittsburgh, PA 2IntroductionUnconstrained Optimization Algorithms Newton Methods Quasi-Newton MethodsConstrained Optimization Karush Kuhn-Tucker Conditions Special Classes of Optimization Problems Reduced Gradient Methods (GRG2, CONOPT, MINOS) Successive Quadratic Programming (SQP) Interior Point MethodsProcess Optimization Black Box Optimization Modular Flowsheet Optimization Infeasible Path The Role of Exact DerivativesLarge-Scale Nonlinear Programming Data Reconciliation Real-time Process OptimizationFurther Applications Sensitivity Analysis for NLP Solutions Multiperiod Optimization ProblemsSummary and ConclusionsNonlinear Programming and Process Optimization3IntroductionOptimization: given a system or process, find the best solution to this process within Function.
Process Design, Prentice Hall, 1997. Numerical Analysis 1. Dennis, J.E. and R. Schnabel, Numerical Methods of Unconstrained Optimization, ... x = -A-1a or x = Vz = -V(Λ-1VTa) Linear Algebra - Eigenvalues. 16 Positive (or Negative) Curvature Positive (or Negative) Definite Hessian Both eigenvalues are strictly positive or negative
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