Applied Nonlinear Programming
Author | : David Mautner Himmelblau |
Publisher | : McGraw-Hill Companies |
Total Pages | : 520 |
Release | : 1972 |
Genre | : Computers |
ISBN | : |
Download Applied Nonlinear Programming Book in PDF, ePub and Kindle
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Applied Nonlinear Programming PDF full book. Access full book title Applied Nonlinear Programming.
Author | : David Mautner Himmelblau |
Publisher | : McGraw-Hill Companies |
Total Pages | : 520 |
Release | : 1972 |
Genre | : Computers |
ISBN | : |
Author | : Sanjay Sharma |
Publisher | : New Age International |
Total Pages | : 16 |
Release | : 2006-12 |
Genre | : Non linear programming |
ISBN | : 812241771X |
Explains the applied nonlinear programming, which has wide spread scientific and industrial applications. This title features: one variable optimization; unconstrained and constrained optimization; geometric programming; and, multi-variable optimization.
Author | : Lorenz T. Biegler |
Publisher | : SIAM |
Total Pages | : 411 |
Release | : 2010-01-01 |
Genre | : Science |
ISBN | : 0898719380 |
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.
Author | : Paul E. Fishback |
Publisher | : CRC Press |
Total Pages | : 410 |
Release | : 2009-12-09 |
Genre | : Business & Economics |
ISBN | : 1420090658 |
Helps Students Understand Mathematical Programming Principles and Solve Real-World Applications Supplies enough mathematical rigor yet accessible enough for undergraduates Integrating a hands-on learning approach, a strong linear algebra focus, MapleTM software, and real-world applications, Linear and Nonlinear Programming with MapleTM: An Interactive, Applications-Based Approach introduces undergraduate students to the mathematical concepts and principles underlying linear and nonlinear programming. This text fills the gap between management science books lacking mathematical detail and rigor and graduate-level books on mathematical programming. Essential linear algebra tools Throughout the text, topics from a first linear algebra course, such as the invertible matrix theorem, linear independence, transpose properties, and eigenvalues, play a prominent role in the discussion. The book emphasizes partitioned matrices and uses them to describe the simplex algorithm in terms of matrix multiplication. This perspective leads to streamlined approaches for constructing the revised simplex method, developing duality theory, and approaching the process of sensitivity analysis. The book also discusses some intermediate linear algebra topics, including the spectral theorem and matrix norms. Maple enhances conceptual understanding and helps tackle problems Assuming no prior experience with Maple, the author provides a sufficient amount of instruction for students unfamiliar with the software. He also includes a summary of Maple commands as well as Maple worksheets in the text and online. By using Maple’s symbolic computing components, numeric capabilities, graphical versatility, and intuitive programming structures, students will acquire a deep conceptual understanding of major mathematical programming principles, along with the ability to solve moderately sized real-world applications. Hands-on activities that engage students Throughout the book, student understanding is evaluated through "waypoints" that involve basic computations or short questions. Some problems require paper-and-pencil calculations; others involve more lengthy calculations better suited for performing with Maple. Many sections contain exercises that are conceptual in nature and/or involve writing proofs. In addition, six substantial projects in one of the appendices enable students to solve challenging real-world problems.
Author | : H. A. Eiselt |
Publisher | : Springer Nature |
Total Pages | : 366 |
Release | : 2019-11-09 |
Genre | : Mathematics |
ISBN | : 3030194620 |
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.
Author | : John T. Betts |
Publisher | : SIAM |
Total Pages | : 442 |
Release | : 2010-01-01 |
Genre | : Mathematics |
ISBN | : 0898716888 |
A focused presentation of how sparse optimization methods can be used to solve optimal control and estimation problems.
Author | : Michael Bartholomew-Biggs |
Publisher | : Springer Science & Business Media |
Total Pages | : 286 |
Release | : 2005-01-04 |
Genre | : Mathematics |
ISBN | : 9781402081101 |
This instructive book introduces the key ideas behind practical nonlinear optimization, accompanied by computational examples and supporting software. It combines computational finance with an important class of numerical techniques.
Author | : Peter Zörnig |
Publisher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 402 |
Release | : 2014-08-22 |
Genre | : Mathematics |
ISBN | : 3110372517 |
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.
Author | : Mokhtar S. Bazaraa |
Publisher | : John Wiley & Sons |
Total Pages | : 867 |
Release | : 2013-06-12 |
Genre | : Mathematics |
ISBN | : 1118626303 |
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.
Author | : Amir Beck |
Publisher | : SIAM |
Total Pages | : 286 |
Release | : 2014-10-27 |
Genre | : Mathematics |
ISBN | : 1611973651 |
This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.