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Author : Jianguo Liu
Publisher :
ISBN 13 :
Total Pages : 308 pages
Book Rating : 4.E/5 ( download)
Download or read book Interior and Exterior Newton Methods for Large-scale Quadratic Programming written by Jianguo Liu and published by . This book was released on 1994 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Stanford University. Department of Operations Research. Systems Optimization Laboratory
Publisher :
ISBN 13 :
Total Pages : 142 pages
Book Rating : 4.F/5 ( download)
Download or read book Barrier Methods for Large-scale Quadratic Programming written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1991 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yurii Nesterov
Publisher : SIAM
ISBN 13 : 9781611970791
Total Pages : 414 pages
Book Rating : 4.9/5 (77 download)
Download or read book Interior-point Polynomial Algorithms in Convex Programming written by Yurii Nesterov and published by SIAM. This book was released on 1994-01-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specialists working in the areas of optimization, mathematical programming, or control theory will find this book invaluable for studying interior-point methods for linear and quadratic programming, polynomial-time methods for nonlinear convex programming, and efficient computational methods for control problems and variational inequalities. A background in linear algebra and mathematical programming is necessary to understand the book. The detailed proofs and lack of "numerical examples" might suggest that the book is of limited value to the reader interested in the practical aspects of convex optimization, but nothing could be further from the truth. An entire chapter is devoted to potential reduction methods precisely because of their great efficiency in practice.
Author : Cornell University. Dept. of Computer Science
Publisher :
ISBN 13 :
Total Pages : 39 pages
Book Rating : 4.:/5 (255 download)
Download or read book An Interior Newton Method for Quadratic Programming written by Cornell University. Dept. of Computer Science and published by . This book was released on 1993 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadratic programming represents an extremely important class of optimization problem. In this paper, we propose a new (interior) approach for the general quadratic programming problem. We establish that our new method is globally and quadratically convergent - published alternative interior approaches do not share such strong convergence properties for the nonconvex case. We also report on the results of preliminary numerical experiments: the results indicate that the proposed method has considerable practical potential.
Author :
Publisher : DIANE Publishing
ISBN 13 : 1428995633
Total Pages : 55 pages
Book Rating : 4.4/5 (289 download)
Download or read book Very large scale optimization written by and published by DIANE Publishing. This book was released on with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gianni Pillo
Publisher : Springer Science & Business Media
ISBN 13 : 0387300651
Total Pages : 297 pages
Book Rating : 4.3/5 (873 download)
Download or read book Large-Scale Nonlinear Optimization written by Gianni Pillo and published by Springer Science & Business Media. This book was released on 2006-06-03 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. Individual chapters, contributed by eminent authorities, provide an up-to-date overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.
Author : Jorge Nocedal
Publisher : Springer Science & Business Media
ISBN 13 : 0387400656
Total Pages : 686 pages
Book Rating : 4.3/5 (874 download)
Download or read book Numerical Optimization written by Jorge Nocedal and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Author : J. M. Ortega
Publisher : Elsevier
ISBN 13 : 1483276724
Total Pages : 593 pages
Book Rating : 4.4/5 (832 download)
Download or read book Iterative Solution of Nonlinear Equations in Several Variables written by J. M. Ortega and published by Elsevier. This book was released on 2014-05-10 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science and Applied Mathematics: Iterative Solution of Nonlinear Equations in Several Variables presents a survey of the basic theoretical results about nonlinear equations in n dimensions and analysis of the major iterative methods for their numerical solution. This book discusses the gradient mappings and minimization, contractions and the continuation property, and degree of a mapping. The general iterative and minimization methods, rates of convergence, and one-step stationary and multistep methods are also elaborated. This text likewise covers the contractions and nonlinear majorants, convergence under partial ordering, and convergence of minimization methods. This publication is a good reference for specialists and readers with an extensive functional analysis background.
Author : Thomas Frederick Coleman
Publisher : SIAM
ISBN 13 : 9780898712681
Total Pages : 278 pages
Book Rating : 4.7/5 (126 download)
Download or read book Large-scale Numerical Optimization written by Thomas Frederick Coleman and published by SIAM. This book was released on 1990-01-01 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers from a workshop held at Cornell University, Oct. 1989, and sponsored by Cornell's Mathematical Sciences Institute. Annotation copyright Book News, Inc. Portland, Or.
Author : Garrett N. Vanderplaats
Publisher : DIANE Publishing
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.:/5 (317 download)
Download or read book Very Large Scale Optimization written by Garrett N. Vanderplaats and published by DIANE Publishing. This book was released on 2002 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Lorenz T. Biegler
Publisher : Springer Science & Business Media
ISBN 13 : 364255508X
Total Pages : 347 pages
Book Rating : 4.6/5 (425 download)
Download or read book Large-Scale PDE-Constrained Optimization written by Lorenz T. Biegler and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal design, optimal control, and parameter estimation of systems governed by partial differential equations (PDEs) give rise to a class of problems known as PDE-constrained optimization. The size and complexity of the discretized PDEs often pose significant challenges for contemporary optimization methods. With the maturing of technology for PDE simulation, interest has now increased in PDE-based optimization. The chapters in this volume collectively assess the state of the art in PDE-constrained optimization, identify challenges to optimization presented by modern highly parallel PDE simulation codes, and discuss promising algorithmic and software approaches for addressing them. These contributions represent current research of two strong scientific computing communities, in optimization and PDE simulation. This volume merges perspectives in these two different areas and identifies interesting open questions for further research.
Author : Neculai Andrei
Publisher : Springer
ISBN 13 : 3319583565
Total Pages : 514 pages
Book Rating : 4.3/5 (195 download)
Download or read book Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology written by Neculai Andrei and published by Springer. This book was released on 2017-12-04 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical optimization models, is introduced to model and solve continuous nonlinear optimization applications. More than 15 real nonlinear optimization applications in algebraic and GAMS representation are presented which are used to illustrate the performances of the algorithms described in this book. Theoretical and computational results, methods, and techniques effective for solving nonlinear optimization problems, are detailed through the algorithms MINOS, KNITRO, CONOPT, SNOPT and IPOPT which work in GAMS technology.
Author : Almerico Murli
Publisher : Springer
ISBN 13 : 0585267782
Total Pages : 158 pages
Book Rating : 4.5/5 (852 download)
Download or read book Computational Issues in High Performance Software for Nonlinear Optimization written by Almerico Murli and published by Springer. This book was released on 2007-06-14 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Issues in High Performance Software for Nonlinear Research brings together in one place important contributions and up-to-date research results in this important area. Computational Issues in High Performance Software for Nonlinear Research serves as an excellent reference, providing insight into some of the most important research issues in the field.
Author : Nicholas I. M. Gould
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (595 download)
Download or read book Numerical Methods for Large-scale Non-convex Quadratic Programming written by Nicholas I. M. Gould and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ciyou Zhu
Publisher :
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.:/5 (254 download)
Download or read book Methods for Large-scale Extended Linear-quadratic Programming written by Ciyou Zhu and published by . This book was released on 1991 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Suvrit Sra
Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)
Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.
Author : Joaquim R. R. A. Martins
Publisher : Cambridge University Press
ISBN 13 : 110898861X
Total Pages : 653 pages
Book Rating : 4.1/5 (89 download)
Download or read book Engineering Design Optimization written by Joaquim R. R. A. Martins and published by Cambridge University Press. This book was released on 2021-11-18 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.
