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Reduced Hessian Successive Quadratic Programming For Realtime Optimization
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Book Synopsis Reduced Hessian Successive Quadratic Programming for Realtime Optimization by : Claudia Schmid
Download or read book Reduced Hessian Successive Quadratic Programming for Realtime Optimization written by Claudia Schmid and published by . This book was released on 1994 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Reduced Hessian Successive Quadratic Programming (SQP) is well suited for the solution of large-scale process optimization problems with many variables and constraints but few degrees of freedom. The reduced space method involves four major steps: an initial preprocessing phase followed by an iterative procedure which requires the solution of a set of nonlinear equations, a QP subproblem and a line search. The overall performance of the algorithm depends directly on the robustness and computational efficiency of the techniques used to handle each of these sub-tasks. Here, we discuss improvements to all of these steps in order to specialize this approach to real-time optimization. A numerical comparison of reduced Hessian SQP with MINOS (Murtagh and Saunders, 1982, 1987) is provided for the optimization of the Sunoco Hydrocracker Fractionation Plant (Bailey et al., 1992). The case study consists of about 3000 variables and constraints and includes several scenarios related to parameter estimation and on-line process-wide optimization. A study of the effect of optimizing the DIB distillation column which constitutes a subproblem of the Sunoco example is also included. The results indicate that our algorithm is at least as robust and an order of magnitude faster than MINOS for this set of problems."
Book Synopsis New Approaches to a Reduced Hessian Successive Quadratic Programming Algorithm for Large-scale Process Optimization by : David J. Ternet
Download or read book New Approaches to a Reduced Hessian Successive Quadratic Programming Algorithm for Large-scale Process Optimization written by David J. Ternet and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reduced Hessian Successive Quadratic Programming for Large-scale Process Optimization by : Claudia Schmid
Download or read book Reduced Hessian Successive Quadratic Programming for Large-scale Process Optimization written by Claudia Schmid and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Approaches to a Reduced Hessian Successive Quadratic Programming Method for Large-scale Process Optimization by : David J. Ternet
Download or read book New Approaches to a Reduced Hessian Successive Quadratic Programming Method for Large-scale Process Optimization written by David J. Ternet and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Reduced Hessian Sequential Quadratic Programming Methods for Multidiscipline Design Optimization by : James P. Masciarelli
Download or read book Reduced Hessian Sequential Quadratic Programming Methods for Multidiscipline Design Optimization written by James P. Masciarelli and published by . This book was released on 1997 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Quadratic Programming Algorithms by : Zdenek Dostál
Download or read book Optimal Quadratic Programming Algorithms written by Zdenek Dostál and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadratic programming (QP) is one advanced mathematical technique that allows for the optimization of a quadratic function in several variables in the presence of linear constraints. This book presents recently developed algorithms for solving large QP problems and focuses on algorithms which are, in a sense optimal, i.e., they can solve important classes of problems at a cost proportional to the number of unknowns. For each algorithm presented, the book details its classical predecessor, describes its drawbacks, introduces modifications that improve its performance, and demonstrates these improvements through numerical experiments. This self-contained monograph can serve as an introductory text on quadratic programming for graduate students and researchers. Additionally, since the solution of many nonlinear problems can be reduced to the solution of a sequence of QP problems, it can also be used as a convenient introduction to nonlinear programming.
Author :Stanford University. Department of Operations Research. Systems Optimization Laboratory Publisher : ISBN 13 : Total Pages :98 pages Book Rating :4.F/5 ( download)
Book Synopsis Large-scale Sequential Quadratic Programming Algorithms by : Stanford University. Department of Operations Research. Systems Optimization Laboratory
Download or read book Large-scale Sequential Quadratic Programming Algorithms written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1992 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Large-scale Sequential Quadratic Programming Algorithms by :
Download or read book Large-scale Sequential Quadratic Programming Algorithms written by and published by . This book was released on 1992 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.
Book Synopsis Advanced Control of Chemical Processes 1994 by : D. Bonvin
Download or read book Advanced Control of Chemical Processes 1994 written by D. Bonvin and published by Elsevier. This book was released on 2014-05-23 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This publication brings together the latest research findings in the key area of chemical process control; including dynamic modelling and simulation - modelling and model validation for application in linear and nonlinear model-based control: nonlinear model-based predictive control and optimization - to facilitate constrained real-time optimization of chemical processes; statistical control techniques - major developments in the statistical interpretation of measured data to guide future research; knowledge-based v model-based control - the integration of theoretical aspects of control and optimization theory with more recent developments in artificial intelligence and computer science.
Book Synopsis Sequential Quadratic Programming Algorithms for Optimization by : Francisco Javier Prieto
Download or read book Sequential Quadratic Programming Algorithms for Optimization written by Francisco Javier Prieto and published by . This book was released on 1989 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Acceleration of Reduced Hessian Methods for Large-scale Nonlinear Programming by : Claudia Schmid
Download or read book Acceleration of Reduced Hessian Methods for Large-scale Nonlinear Programming written by Claudia Schmid and published by . This book was released on 1992 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Process optimization problems are frequently characterized by large models, with many variables and constraints but relatively few degrees of freedom. Thus, reduced Hessian decomposition methods applied to Successive Quadratic Programming (SQP) exploit the low dimensionality of the subspace of the decision variables, and have been very successful for a wide variety of process application. However, further development is needed for improving the efficient large-scale use of these tools. In this study we develop an improved SQP algorithm decomposition with coordinate bases that includes an inexpensive second order correction term. The resulting algorithm is 1-step Q-superlinearly convergent. More importantly, though, the resulting algorithm is largely independent of the specific decomposition steps. Thus, the inexpensive factorization of the coordinate decomposition, which lends itself very well to tailoring, can be applied in a reliable and efficient manner. With this efficient and easy-to-implement NLP strategy, we continue to improve the efficiency of the optimization algorithm by exploiting the mathematical structure of existing process engineering models. Here we consider the tailoring of a reduced Hessian method for the block tridiagonal structure of the model equations for distillation columns. This approach is applied to the Naphthali-Sandholm algorithm implemented within the UNIDIST and programs. Our reduced Hessian SQP strategy is incorporated within the package with only minor changes in the program's interface and data structures. Through this integration, reductions of 20% to 80% in the total CPU time are obtained compared to general reduced space optimization; an order of magnitude reduction is obtained when compared to conventional sequential strategies. Consequently, this approach shows considerable potential for efficient and reliable large-scale process optimization, particularly when complex Newton-based process models are already available."
Book Synopsis A Regularized Active-Set method For Sparse Convex Quadratic Programming by :
Download or read book A Regularized Active-Set method For Sparse Convex Quadratic Programming written by and published by Stanford University. This book was released on with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Quadratic Programming Methods for Tailored Reduced Hessian SQP by : Claudia Schmid
Download or read book Quadratic Programming Methods for Tailored Reduced Hessian SQP written by Claudia Schmid and published by . This book was released on 1993 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advanced Control of Chemical Processes by :
Download or read book Advanced Control of Chemical Processes written by and published by . This book was released on 1991 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Inertia-controlling Methods for Quadratic Programming by : Philip E. Gill
Download or read book Inertia-controlling Methods for Quadratic Programming written by Philip E. Gill and published by . This book was released on 1988 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We also derive recurrance relations that facilitate the efficient implementation of a class of inertia-controlling methods that maintain the factorization of a nonsingular matrix associated with the Karush-Kuhn-Tucker conditions."
Book Synopsis Reduced Successive Quadratic Programming in Hilbert Space with Applications to Optimal Control by : Frank-Stephan Kupfer
Download or read book Reduced Successive Quadratic Programming in Hilbert Space with Applications to Optimal Control written by Frank-Stephan Kupfer and published by . This book was released on 1992 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Large-Scale Optimization with Applications by :
Download or read book Large-Scale Optimization with Applications written by and published by Springer Science & Business Media. This book was released on 1997 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
