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Nonlinear Programming

Nonlinear Programming
Author: Dimitri P. Bertsekas
Publisher: Goodman Publishers
Total Pages: 808
Release: 1999
Genre: Mathematics
ISBN:

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Nonlinear Programming

Nonlinear Programming
Author: Mokhtar S. Bazaraa
Publisher: John Wiley & Sons
Total Pages: 867
Release: 2013-06-12
Genre: Mathematics
ISBN: 1118626303

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COMPREHENSIVE COVERAGE OF NONLINEAR PROGRAMMING THEORY AND ALGORITHMS, THOROUGHLY REVISED AND EXPANDED Nonlinear Programming: Theory and Algorithms—now in an extensively updated Third Edition—addresses the problem of optimizing an objective function in the presence of equality and inequality constraints. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction. Concentration on the three major parts of nonlinear programming is provided: Convex analysis with discussion of topological properties of convex sets, separation and support of convex sets, polyhedral sets, extreme points and extreme directions of polyhedral sets, and linear programming Optimality conditions and duality with coverage of the nature, interpretation, and value of the classical Fritz John (FJ) and the Karush-Kuhn-Tucker (KKT) optimality conditions; the interrelationships between various proposed constraint qualifications; and Lagrangian duality and saddle point optimality conditions Algorithms and their convergence, with a presentation of algorithms for solving both unconstrained and constrained nonlinear programming problems Important features of the Third Edition include: New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more Updated discussion and new applications in each chapter Detailed numerical examples and graphical illustrations Essential coverage of modeling and formulating nonlinear programs Simple numerical problems Advanced theoretical exercises The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques. The logical and self-contained format uniquely covers nonlinear programming techniques with a great depth of information and an abundance of valuable examples and illustrations that showcase the most current advances in nonlinear problems.


Linear and Nonlinear Programming

Linear and Nonlinear Programming
Author: David G. Luenberger
Publisher: Springer Science & Business Media
Total Pages: 546
Release: 2008-06-20
Genre: Business & Economics
ISBN: 0387745033

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This third edition of the classic textbook in Optimization has been fully revised and updated. It comprehensively covers modern theoretical insights in this crucial computing area, and will be required reading for analysts and operations researchers in a variety of fields. The book connects the purely analytical character of an optimization problem, and the behavior of algorithms used to solve it. Now, the third edition has been completely updated with recent Optimization Methods. The book also has a new co-author, Yinyu Ye of California’s Stanford University, who has written lots of extra material including some on Interior Point Methods.


Nonlinear Programming

Nonlinear Programming
Author: Lorenz T. Biegler
Publisher: SIAM
Total Pages: 411
Release: 2010-01-01
Genre: Science
ISBN: 0898719380

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This book addresses modern nonlinear programming (NLP) concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. The author provides a firm grounding in fundamental NLP properties and algorithms, and relates them to real-world problem classes in process optimization, thus making the material understandable and useful to chemical engineers and experts in mathematical optimization.


The Mathematics of Nonlinear Programming

The Mathematics of Nonlinear Programming
Author: Anthony L. Peressini
Publisher: Springer
Total Pages: 0
Release: 2012-09-30
Genre: Mathematics
ISBN: 9781461269892

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Nonlinear programming provides an excellent opportunity to explore an interesting variety of pure and solidly applicable mathematics, numerical analysis, and computing. This text develops some of the ideas and techniques involved in the optimization methods using calculus, leading to the study of convexity. This is followed by material on basic numerical methods, least squares, the Karush-Kuhn-Tucker theorem, penalty functions, and Lagrange multipliers. The authors have aimed their presentation at the student who has a working knowledge of matrix algebra and advanced calculus, but has had no previous exposure to optimization.


Nonlinear Optimization

Nonlinear Optimization
Author: H. A. Eiselt
Publisher: Springer Nature
Total Pages: 366
Release: 2019-11-09
Genre: Mathematics
ISBN: 3030194620

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This book provides a comprehensive introduction to nonlinear programming, featuring a broad range of applications and solution methods in the field of continuous optimization. It begins with a summary of classical results on unconstrained optimization, followed by a wealth of applications from a diverse mix of fields, e.g. location analysis, traffic planning, and water quality management, to name but a few. In turn, the book presents a formal description of optimality conditions, followed by an in-depth discussion of the main solution techniques. Each method is formally described, and then fully solved using a numerical example.


Nonlinear Integer Programming

Nonlinear Integer Programming
Author: Duan Li
Publisher: Springer Science & Business Media
Total Pages: 452
Release: 2006-08-13
Genre: Mathematics
ISBN: 0387329951

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A combination of both Integer Programming and Nonlinear Optimization, this is a powerful book that surveys the field and provides a state-of-the-art treatment of Nonlinear Integer Programming. It is the first book available on the subject. The book aims to bring the theoretical foundation and solution methods for nonlinear integer programming to students and researchers in optimization, operations research, and computer science.


Nonlinear Programming

Nonlinear Programming
Author: Peter Zörnig
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 402
Release: 2014-08-22
Genre: Mathematics
ISBN: 3110372517

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This book is an introduction to nonlinear programming. It deals with the theoretical foundations and solution methods, beginning with the classical procedures and reaching up to “modern” methods like trust region methods or procedures for nonlinear and global optimization. A comprehensive bibliography including diverse web sites with information about nonlinear programming, in particular software, is presented. Without sacrificing the necessary mathematical rigor, excessive formalisms are avoided. Several examples, exercises with detailed solutions, and applications are provided, making the text adequate for individual studies. The book is written for students from the fields of applied mathematics, engineering, economy, and computation.


Linear and Nonlinear Programming

Linear and Nonlinear Programming
Author: Stephen G. Nash
Publisher: McGraw-Hill Science, Engineering & Mathematics
Total Pages: 744
Release: 1996
Genre: Computers
ISBN:

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A complete and unified introduction to applications, theory and algorithms which contains modelling examples, computer based exercises and material on interior point methods and trust-region methods. Gives both numerical methods for optimisation and optomisation problems.


Nonlinear Optimization

Nonlinear Optimization
Author: Andrzej Ruszczynski
Publisher: Princeton University Press
Total Pages: 464
Release: 2011-09-19
Genre: Mathematics
ISBN: 1400841054

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Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects, Nonlinear Optimization is the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion, with detailed and easy-to-follow proofs illustrated by numerous examples and figures. The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern topics such as optimality conditions and numerical methods for problems involving nondifferentiable functions, semidefinite programming, metric regularity and stability theory of set-constrained systems, and sensitivity analysis of optimization problems. Based on a decade's worth of notes the author compiled in successfully teaching the subject, this book will help readers to understand the mathematical foundations of the modern theory and methods of nonlinear optimization and to analyze new problems, develop optimality theory for them, and choose or construct numerical solution methods. It is a must for anyone seriously interested in optimization.