Titlebook: Large-Scale Optimization with Applications; Part II: Optimal Des Lorenz T. Biegler,Thomas F. Coleman,Fadil N. Santo Book 1997 Springer-Verl

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Experience with a Sparse Nonlinear Programming Algorithmdinary or partial differential equations. For applications of this type the number of variables and constraints may be large (i.e. 100 < n < 100000), and the corresponding Jacobian and Hessian matrices are very sparse (i.e. typically less than 1% of the elements are nonzero). For small problems with

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Mixed-Integer Nonlinear Programming: A Survey of Algorithms and Applicationsr-Approximation, Generalized Benders and Extended Cutting Plane methods as applied to nonlinear discrete optimization problems that are expressed in algebraic form. The extension of these methods is also considered for logic based representations. Finally, an overview of the applications in many are

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Some Recent Developments in Computational Optimal Controle. they are based on some type of problem discretization and require nonlinear programming techniques to determine the optimal solution within certain finite-dimensional parameter spaces..The first method is called Trajectory Optimization via Differential Inclusion (TODI). This method can be viewed

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Large-Scale SQP Methods for Optimization of Navier-Stokes Flowson of fluid on portions of the boundary, and the objective function represents the rate at which energy is dissipated in the fluid. We show how reduced Hessian successive quadratic programming methods, which avoid converging the flow equations at each iteration, can be tailored to these problems. Bo

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