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Nonlinear Programming: Concepts, Algorithms and Applications

Nonlinear Programming: Concepts, Algorithms and ApplicationsL. T. BieglerChemical Engineering DepartmentCarnegie Mellon UniversityPittsburgh, PA 2 IntroductionUnconstrained 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 Optimization3 IntroductionOptimization: given a system or process, find the best solution to this process w

Mathematician - characterization of theoretical properties of optimization, convergence, existence, local convergence rates. Numerical Analyst - implementation of optimization method for efficient and "practical" use. Concerned with ease of computations, numerical stability, performance. Engineer - applies optimization method to real problems.

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