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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火車車輪

A Multiplier-Free, Reduced Hessian Method for Process Optimizationhrough the use of sparse matrix factorizations. The algorithm has the same superlinear and global properties as the reduced Hessian method developed in [4]. Here we summarize these properties and demonstrate the performance of the multiplier-free SQP method through numerical experiments.

Grasping

Numerical Optimal Control of Parabolic PDES Using DASOPTr DAEs. Special techniques are needed in order to solve this very large optimal control problem. The use of DASOPT is illustrated by its application to a nonlinear parabolic PDE boundary control problem in two spatial dimensions. Computational results with and without bounds on the state variables are presented.

過份艷麗

CRACK

Deterministic Global Optimization in Design, Control, and Computational Chemistrye nonlinear optimization problems. For the majority of the presented methods nondistributed global optimization approaches are discussed with the exception of decomposition-based methods where a distributed global optimization approach is presented.

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規(guī)范就好

The Development of the SQP Algorithm for Nonlinear Programmingand ensuring global and superlinear convergence. It then discusses the problems which arise in applying the SQP algorithm to large-scale problems, and finally describes a new algorithm which circumvents these problems.

萬靈丹

Some Aspects of Sequential Quadratic Programming Methodscurrently the method of choice when solving small or medium-sized problems. Over the last fifteen years several implementations have been written to solve specific applications in which large problems arise. Recently there have been some general purpose implementations..We focus on two aspects of SQ