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| nonlinear programming real life applications: Nonlinear Programming Lorenz T. Biegler, 2010-10-14 A comprehensive treatment of nonlinear programming concepts and algorithms, especially as they apply to challenging applications in chemical process engineering. |
| nonlinear programming real life applications: Selected Applications of Nonlinear Programming Jerome Bracken, Garth P. McCormick, 1968 |
| nonlinear programming real life applications: Practical Methods for Optimal Control and Estimation Using Nonlinear Programming John T. Betts, 2010-01-01 The book describes how sparse optimization methods can be combined with discretization techniques for differential-algebraic equations and used to solve optimal control and estimation problems. The interaction between optimization and integration is emphasized throughout the book. |
| nonlinear programming real life applications: Mixed Integer Nonlinear Programming Jon Lee, Sven Leyffer, 2011-12-02 Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances. |
| nonlinear programming real life applications: Linear and Nonlinear Inverse Problems with Practical Applications Jennifer L. Mueller, Samuli Siltanen, 2012-11-30 Inverse problems arise in practical applications whenever there is a need to interpret indirect measurements. This book explains how to identify ill-posed inverse problems arising in practice and gives a hands-on guide to designing computational solution methods for them, with related codes on an accompanying website. The guiding linear inversion examples are the problem of image deblurring, x-ray tomography, and backward parabolic problems, including heat transfer. A thorough treatment of electrical impedance tomography is used as the guiding nonlinear inversion example which combines the analytic-geometric research tradition and the regularization-based school of thought in a fruitful manner. This book is complete with exercises and project topics, making it ideal as a classroom textbook or self-study guide for graduate and advanced undergraduate students in mathematics, engineering or physics who wish to learn about computational inversion. It also acts as a useful guide for researchers who develop inversion techniques in high-tech industry. |
| nonlinear programming real life applications: Nonlinear Optimization H. A. Eiselt, Carl-Louis Sandblom, 2019-11-09 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 programming real life applications: Combinatorial, Linear, Integer and Nonlinear Optimization Apps J. MacGregor Smith, 2022-11-01 This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN). Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and related mathematics. |
| nonlinear programming real life applications: Linear and Nonlinear Programming David G. Luenberger, Yinyu Ye, 2008-07-07 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 real life applications: Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming Mohit Tawarmalani, Nikolaos V. Sahinidis, 2013-04-17 Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models. Both of these extensions of the linear programming model are NP-hard, thus representing very challenging problems. On the brighter side, recent advances in algorithmic and computing technology make it possible to re visit these problems with the hope of solving practically relevant problems in reasonable amounts of computational time. Initial attempts at solving nonlinear programs concentrated on the de velopment of local optimization methods guaranteeing globality under the assumption of convexity. On the other hand, the integer programming liter ature has concentrated on the development of methods that ensure global optima. The aim of this book is to marry the advancements in solving nonlinear and integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal of devising practically efficient global optimization algorithms for MINLPs. |
| nonlinear programming real life applications: Nonlinear Programming Mordecai Avriel, 2003-01-01 This overview provides a single-volume treatment of key algorithms and theories. Begins with the derivation of optimality conditions and discussions of convex programming, duality, generalized convexity, and analysis of selected nonlinear programs, and then explores techniques for numerical solutions and unconstrained optimization methods. 1976 edition. Includes 58 figures and 7 tables. |
| nonlinear programming real life applications: Enterprise Information Systems VII Chin-Sheng Chen, 2006-09-28 The purpose of the 7th International Conference on Enterprise Information Systems (ICEIS) was to bring together researchers, engineers and practitioners interested in the advances and business applications of information systems. Five simultaneous tracks have been held, covering different aspects of Enterprise Information Systems Applications, including Enterprise Database Technology, Systems Integration, Artificial Intelligence, Decision Support Systems, Information Systems Analysis and Specification, Internet Computing, Electronic Commerce and Human Factors. ICEIS focuses on real world applications: therefore authors were asked to highlight the benefits of Information Technology for industry and services. During the conference there was an interesting debate on how to solve business problems, using IT. Paper presentations included the description of advanced prototypes, systems, tools and techniques as well as general surveys indicating future directions for information systems and technologies. Papers included in the book are the best papers presented at the ICEIS 2005 conference. |
| nonlinear programming real life applications: Nonlinear Multiobjective Optimization Kaisa Miettinen, 2012-12-06 Problems with multiple objectives and criteria are generally known as multiple criteria optimization or multiple criteria decision-making (MCDM) problems. So far, these types of problems have typically been modelled and solved by means of linear programming. However, many real-life phenomena are of a nonlinear nature, which is why we need tools for nonlinear programming capable of handling several conflicting or incommensurable objectives. In this case, methods of traditional single objective optimization and linear programming are not enough; we need new ways of thinking, new concepts, and new methods - nonlinear multiobjective optimization. Nonlinear Multiobjective Optimization provides an extensive, up-to-date, self-contained and consistent survey, review of the literature and of the state of the art on nonlinear (deterministic) multiobjective optimization, its methods, its theory and its background. The amount of literature on multiobjective optimization is immense. The treatment in this book is based on approximately 1500 publications in English printed mainly after the year 1980. Problems related to real-life applications often contain irregularities and nonsmoothnesses. The treatment of nondifferentiable multiobjective optimization in the literature is rather rare. For this reason, this book contains material about the possibilities, background, theory and methods of nondifferentiable multiobjective optimization as well. This book is intended for both researchers and students in the areas of (applied) mathematics, engineering, economics, operations research and management science; it is meant for both professionals and practitioners in many different fields of application. The intention has been to provide a consistent summary that may help in selecting an appropriate method for the problem to be solved. It is hoped the extensive bibliography will be of value to researchers. |
| nonlinear programming real life applications: Control Applications of Nonlinear Programming H. E. Rauch, 2014-05-23 Control Applications of Nonlinear Programming contains the proceedings of the International Federation of Automatic Control Workshop on Control Applications of Nonlinear Programming, held in Denver, Colorado, on June 21, 1979. The workshop provided a forum for discussing the application of optimal and nonlinear programming techniques to real-life control problems. The volume covers a variety of specific applications ranging from microprocessor control of automotive engines and optimal design of structures to optimal aircraft trajectories, system identification, and robotics. Comprised of 14 chapters, this book begins by describing the application of nonlinear programming to an optimum design problem coming from mechanical engineering. The reader is then introduced to a nonlinear regulator design for magnetic suspension; optimal control solution of the automotive emission-constrained minimum fuel problem; and nonlinear programming for system identification. Subsequent chapters focus on mathematical programming algorithms based on Lagrangian functions for solving optimal control problems; computer-aided design via optimization; optimal and suboptimal control of oscillating dynamical systems; and the application of nonlinear programming to the solution of optimal output-constrained regulator problems. This monograph will be of interest to mathematicians, computer scientists, and engineers. |
| nonlinear programming real life applications: Nonlinear and Dynamic Programming S. Dano, 2012-12-06 This book is intended to provide an introductory text of Nonlinear and Dynamic Programming for students of managerial economics and operations research. The author also hopes that engineers, business executives, managers, and others responsible for planning of industrial operations may find it useful as a guide to the problems and methods treated, with a view to practical applications. The book may be considered as a sequel to the author's Linear Programming in Industry (1960, 4th revised and enlarged edition 1974), but it can be used independently by readers familiar with the elements of linear programming models and techniques. The two volumes con stitute an introduction to the methods of mathematical programming and their application to industrial optimization problems. The author feels that the vast and ever-increasing literature on mathematical programming has not rendered an introductory exposition super fluous. The general student often tends to feel somewhat lost if he goes straight to the special literature; he will be better equipped for tackling real problems and using computer systems if he has acquired some previous training in constructing small-scale programming models and applying standard algorithms for solving them by hand. The book is intended to provide this kind of training, keeping the mathematics at the necessary minimum. The text contains numerous exercises. The reader should work out these problems for himself and check with the answers given at the end of the book. The text is based on lectures given at the University of Copenhagen. |
| nonlinear programming real life applications: Nonlinear Optimization Applications Using the GAMS Technology Neculai Andrei, 2013-06-22 Here is a collection of nonlinear optimization applications from the real world, expressed in the General Algebraic Modeling System (GAMS). The concepts are presented so that the reader can quickly modify and update them to represent real-world situations. |
| nonlinear programming real life applications: Nonlinear Optimization William P. Fox, 2020-12-08 Optimization is the act of obtaining the best result under given circumstances. In design, construction, and maintenance of any engineering system, engineers must make technological and managerial decisions to minimize either the effort or cost required or to maximize benefits. There is no single method available for solving all optimization problems efficiently. Several optimization methods have been developed for different types of problems. The optimum-seeking methods are mathematical programming techniques (specifically, nonlinear programming techniques). Nonlinear Optimization: Models and Applications presents the concepts in several ways to foster understanding. Geometric interpretation: is used to re-enforce the concepts and to foster understanding of the mathematical procedures. The student sees that many problems can be analyzed, and approximate solutions found before analytical solutions techniques are applied. Numerical approximations: early on, the student is exposed to numerical techniques. These numerical procedures are algorithmic and iterative. Worksheets are provided in Excel, MATLAB®, and MapleTM to facilitate the procedure. Algorithms: all algorithms are provided with a step-by-step format. Examples follow the summary to illustrate its use and application. Nonlinear Optimization: Models and Applications: Emphasizes process and interpretation throughout Presents a general classification of optimization problems Addresses situations that lead to models illustrating many types of optimization problems Emphasizes model formulations Addresses a special class of problems that can be solved using only elementary calculus Emphasizes model solution and model sensitivity analysis About the author: William P. Fox is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School. He received his Ph.D. at Clemson University and has taught at the United States Military Academy and at Francis Marion University where he was the chair of mathematics. He has written many publications, including over 20 books and over 150 journal articles. Currently, he is an adjunct professor in the Department of Mathematics at the College of William and Mary. He is the emeritus director of both the High School Mathematical Contest in Modeling and the Mathematical Contest in Modeling. |
| nonlinear programming real life applications: Linear Complementarity, Linear and Nonlinear Programming Katta G. Murty, 1988 |
| nonlinear programming real life applications: Nonlinear Optimization with Engineering Applications Michael Bartholomew-Biggs, 2008-12-16 This textbook examines a broad range of problems in science and engineering, describing key numerical methods applied to real life. The case studies presented are in such areas as data fitting, vehicle route planning and optimal control, scheduling and resource allocation, sensitivity calculations and worst-case analysis. Chapters are self-contained with exercises provided at the end of most sections. Nonlinear Optimization with Engineering Applications is ideal for self-study and classroom use in engineering courses at the senior undergraduate or graduate level. The book will also appeal to postdocs and advanced researchers interested in the development and use of optimization algorithms. |
| nonlinear programming real life applications: Linear and Nonlinear Optimization Richard W. Cottle, Mukund N. Thapa, 2018-05-12 This textbook on Linear and Nonlinear Optimization is intended for graduate and advanced undergraduate students in operations research and related fields. It is both literate and mathematically strong, yet requires no prior course in optimization. As suggested by its title, the book is divided into two parts covering in their individual chapters LP Models and Applications; Linear Equations and Inequalities; The Simplex Algorithm; Simplex Algorithm Continued; Duality and the Dual Simplex Algorithm; Postoptimality Analyses; Computational Considerations; Nonlinear (NLP) Models and Applications; Unconstrained Optimization; Descent Methods; Optimality Conditions; Problems with Linear Constraints; Problems with Nonlinear Constraints; Interior-Point Methods; and an Appendix covering Mathematical Concepts. Each chapter ends with a set of exercises. The book is based on lecture notes the authors have used in numerous optimization courses the authors have taught at Stanford University. It emphasizes modeling and numerical algorithms for optimization with continuous (not integer) variables. The discussion presents the underlying theory without always focusing on formal mathematical proofs (which can be found in cited references). Another feature of this book is its inclusion of cultural and historical matters, most often appearing among the footnotes. This book is a real gem. The authors do a masterful job of rigorously presenting all of the relevant theory clearly and concisely while managing to avoid unnecessary tedious mathematical details. This is an ideal book for teaching a one or two semester masters-level course in optimization – it broadly covers linear and nonlinear programming effectively balancing modeling, algorithmic theory, computation, implementation, illuminating historical facts, and numerous interesting examples and exercises. Due to the clarity of the exposition, this book also serves as a valuable reference for self-study. Professor Ilan Adler, IEOR Department, UC Berkeley A carefully crafted introduction to the main elements and applications of mathematical optimization. This volume presents the essential concepts of linear and nonlinear programming in an accessible format filled with anecdotes, examples, and exercises that bring the topic to life. The authors plumb their decades of experience in optimization to provide an enriching layer of historical context. Suitable for advanced undergraduates and masters students in management science, operations research, and related fields. Michael P. Friedlander, IBM Professor of Computer Science, Professor of Mathematics, University of British Columbia |
| nonlinear programming real life applications: Nonlinear Programming Dimitri P. Bertsekas, 1999 |
| nonlinear programming real life applications: Nonlinear Programming Anthony V. Fiacco, Garth P. McCormick, 1990-01-01 Analyzes the 'central' or 'dual' trajectory used by modern path following and primal/dual methods for convex / general linear programming. |
| nonlinear programming real life applications: Real Life Applications of Soft Computing Anupam Shukla, Ritu Tiwari, Rahul Kala, 2010-05-21 Rapid advancements in the application of soft computing tools and techniques have proven valuable in the development of highly scalable systems and resulted in brilliant applications, including those in biometric identification, interactive voice response systems, and data mining. Although many resources on the subject adequately cover the theoreti |
| nonlinear programming real life applications: Real-World Applications of Evolutionary Computing Stefano Cagnoni, Riccardo Poli, George D. Smith, David Corne, Martin Oates, Emma Hart, Pier L. Lanzi, Egbert J. Willem, Yun Li, Ben Paechter, Terence C. Fogarty, 2003-07-31 The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems. |
| nonlinear programming real life applications: Practical Numerical and Scientific Computing with MATLAB® and Python Eihab B. M. Bashier, 2020-03-18 Practical Numerical and Scientific Computing with MATLAB® and Python concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python. |
| nonlinear programming real life applications: Linear and Combinatorial Programming Katta G. Murty, 1985 |
| nonlinear programming real life applications: Nonlinear Programming Mokhtar S. Bazaraa, Hanif D. Sherali, C. M. Shetty, 2013-06-12 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. |
| nonlinear programming real life applications: Non-Linear Programming Nita H. Shah, Poonam Prakash Mishra, 2020-12-16 This book is for beginners who are struggling to understand and optimize non-linear problems. The content will help readers gain an understanding and learn how to formulate real-world problems and will also give insight to many researchers for their future prospects. It proposes a mind map for conceptual understanding and includes sufficient solved examples for reader comprehension. The theory is explained in a lucid way. The variety of examples are framed to raise the thinking level of the reader and the formulation of real-world problems are included in the last chapter along with applications. The book is self-explanatory, well synchronized and written for undergraduate, post graduate and research scholars. |
| nonlinear programming real life applications: Nonlinear Programming Peter Zörnig, 2014-01-31 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. |
| nonlinear programming real life applications: Lectures on Modern Convex Optimization Aharon Ben-Tal, Arkadi Nemirovski, 2001-01-01 Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications. |
| nonlinear programming real life applications: Nonlinear Optimization with Financial Applications Michael Bartholomew-Biggs, 2005-01-04 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. |
| nonlinear programming real life applications: Introduction to Nonlinear Optimization Amir Beck, 2023-06-29 Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author’s objective is to provide the foundations of theory and algorithms of nonlinear optimization as well as to present a variety of applications from diverse areas of applied sciences. Introduction to Nonlinear Optimization gradually yet rigorously builds connections between theory, algorithms, applications, and actual implementation. The book contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares. Readers will discover a wide array of applications such as circle fitting, Chebyshev center, the Fermat–Weber problem, denoising, clustering, total least squares, and orthogonal regression. These applications are studied both theoretically and algorithmically, illustrating concepts such as duality. Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used. More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples. This book is intended for graduate or advanced undergraduate students in mathematics, computer science, electrical engineering, and potentially other engineering disciplines. |
| nonlinear programming real life applications: More Test Examples for Nonlinear Programming Codes Klaus Schittkowski, 2012-12-06 This collection of 188 nonlinear programming test examples is a supplement of the test problem collection published by Hock and Schittkowski [2]. As in the former case, the intention is to present an extensive set of nonlinear programming problems that were used by other authors in the past to develop, test or compare optimization algorithms. There is no distinction between an easy or difficult test problem, since any related classification must depend on the underlying algorithm and test design. For instance, a nonlinear least squares problem may be solved easily by a special purpose code within a few iterations, but the same problem can be unsolvable for a general nonlinear programming code due to ill-conditioning. Thus one should consider both collections as a possible offer to choose some suitable problems for a specific test frame. One difference between the new collection and the former one pub lished by Hock and Schittkowski [2], is the attempt to present some more realistic or real world problems. Moreover a couple of non linear least squares test problems were collected which can be used e. g. to test data fitting algorithms. The presentation of the test problems is somewhat simplified and numerical solutions are computed only by one nonlinear programming code, the sequential quadratic programming algorithm NLPQL of Schittkowski [3]. But both test problem collections are implemeted in the same way in form of special FORTRAN subroutines, so that the same test programs can be used. |
| nonlinear programming real life applications: Practical Methods of Optimization R. Fletcher, 2013-06-06 Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers revised coverage of basic theory and standard techniques, with updated discussions of line search methods, Newton and quasi-Newton methods, and conjugate direction methods, as well as a comprehensive treatment of restricted step or trust region methods not commonly found in the literature. Also includes recent developments in hybrid methods for nonlinear least squares; an extended discussion of linear programming, with new methods for stable updating of LU factors; and a completely new section on network programming. Chapters include computer subroutines, worked examples, and study questions. |
| nonlinear programming real life applications: Linear Programming Robert J Vanderbei, 2013-07-16 This Fourth Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with a substantial treatment of linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Readers will discover a host of practical business applications as well as non-business applications. Topics are clearly developed with many numerical examples worked out in detail. Specific examples and concrete algorithms precede more abstract topics. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered, including the two-phase simplex method, primal-dual simplex method, path-following interior-point method, and homogeneous self-dual methods. In addition, the author provides online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's website. The website also includes new online instructional tools and exercises. |
| nonlinear programming real life applications: Handbook of Real-World Applications in Modeling and Simulation John A. Sokolowski, Catherine M. Banks, 2012-04-24 Introduces various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges facing society Handbook of Real-World Applications in Modeling and Simulation provides a thorough explanation of modeling and simulation in the most useful, current, and predominant applied areas of transportation, homeland security, medicine, operational research, military science, and business modeling. Offering a cutting-edge and accessible presentation, this book discusses how and why the presented domains have become leading applications of modeling and simulation techniques. Contributions from leading academics and researchers integrate modeling and simulation theories, methods, and data to analyze challenges that involve technological and social issues. The book begins with an introduction that explains why modeling and simulation is a reliable analysis assessment tool for complex systems problems. Subsequent chapters provide an orientation to various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges across real-world applied domains. Additionally, the handbook: Provides a practical one-stop reference on modeling and simulation and contains an accessible introduction to key concepts and techniques Introduces, trains, and prepares readers from statistics, mathematics, engineering, computer science, economics, and business to use modeling and simulation in their studies and research Features case studies that are representative of fundamental areas of multidisciplinary studies and provides a concise look at the key concepts of modeling and simulation Contains a collection of original ideas on modeling and simulation to help academics and practitioners develop a multifunctional perspective Self-contained chapters offer a comprehensive approach to explaining each respective domain and include sections that explore the related history, theory, modeling paradigms, and case studies. Key terms and techniques are clearly outlined, and exercise sets allow readers to test their comprehension of the presented material. Handbook of Real-World Applications in Modeling and Simulation is an essential reference for academics and practitioners in the areas of operations research, business, management science, engineering, statistics, mathematics, and computer science. The handbook is also a suitable supplement for courses on modeling and simulation at the graduate level. |
| nonlinear programming real life applications: Linear and Nonlinear Optimization Igor Griva, Stephen G. Nash, Ariela Sofer, 2009-01-01 Provides an introduction to the applications, theory, and algorithms of linear and nonlinear optimization. The emphasis is on practical aspects - discussing modern algorithms, as well as the influence of theory on the interpretation of solutions or on the design of software. The book includes several examples of realistic optimization models that address important applications. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. The book is designed to be flexible. It has a modular structure, and uses consistent notation and terminology throughout. It can be used in many different ways, in many different courses, and at many different levels of sophistication. |
| nonlinear programming real life applications: The Mathematics of Nonlinear Programming Anthony L. Peressini, Francis E. Sullivan, J.J. Jr. Uhl, 2012-09-30 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 programming real life applications: Applications of Stochastic Programming Stein W. Wallace, William T. Ziemba, 2005-01-01 Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity. |
| nonlinear programming real life applications: Practical Optimization Andreas Antoniou, Wu-Sheng Lu, 2007-12-14 Practical Optimization: Algorithms and Engineering Applications provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes the book suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course. Each half of the book contains a full semester’s worth of complementary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable for practitioners in the field. Advancements in the efficiency of digital computers and the evolution of reliable software for numerical computation during the past three decades have led to a rapid growth in the theory, methods, and algorithms of numerical optimization. This body of knowledge has motivated widespread applications of optimization methods in many disciplines, e.g., engineering, business, and science, and has subsequently led to problem solutions that were considered intractable not too long ago. |
| nonlinear programming real life applications: Advances and Trends in Optimization with Engineering Applications Tamas Terlaky, Miguel F. Anjos, Shabbir Ahmed, 2017-04-26 Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods. |
Home | Nonlinear Dynamics - Springer
Nonlinear Dynamics is a hybrid journal publishing original content at the forefront of nonlinear dynamic research across diverse systems and scales. The journal covers nonlinear dynamics …
Methods in Nonlinear Analysis - SpringerLink
Theories, techniques and results in many different branches of mathematics have been combined in solving nonlinear problems. This book collects and reorganizes up-to-date materials …
Nonlinear Acoustics - SpringerLink
Chapters 10 through 15 cover applications and additional methodologies encountered in nonlinear acoustics that include perturbation and numerical methods, ray theory for inhomogeneous …
Home | Journal of Nonlinear Science - Springer
The mission of the Journal of Nonlinear Science is to publish papers that augment the fundamental ways we describe, model, and predict nonlinear phenomena. It features papers …
Nonlinear Systems: Analysis, Stability, and Control | SpringerLink
Coupled with this set of analytic advances has been the vast increase in computational power available for both the simulation and visualization of nonlinear systems as well as for the …
Articles | Nonlinear Dynamics - Springer
4 days ago · Nonlinear Dynamics is a hybrid journal publishing original content at the forefront of nonlinear dynamic research across diverse systems and scales. The ...
Nonlinear Dynamics: A Concise Introduction Interlaced with Code ...
This concise and up-to-date textbook provides an accessible introduction to the core concepts of nonlinear dynamics as well as its existing and potential applications. The book is aimed at …
Data-driven nonlinear and stochastic dynamics with control
Dec 16, 2024 · The analysis is developed with reference to a nonlinear beam where the two boundary conditions have nonlinearities and masses, with the goal of identifying the uncertain …
Lectures on Nonlinear Dynamics - SpringerLink
This book presents a compilation of lectures delivered at the São Paulo School of Advanced Sciences on Nonlinear Dynamics, categorized into four groups: parametric resonance, …
Aims and scope | Nonlinear Dynamics - Springer
Nonlinear Dynamics provides a forum for the rapid publication of original research in the field of nonlinear dynamics. The scope of the journal encompasses all nonlinear dynamic phenomena …
Home | Nonlinear Dynamics - Springer
Nonlinear Dynamics is a hybrid journal publishing original content at the forefront of nonlinear dynamic research across diverse systems and scales. The journal covers nonlinear dynamics …
Methods in Nonlinear Analysis - SpringerLink
Theories, techniques and results in many different branches of mathematics have been combined in solving nonlinear problems. This book collects and reorganizes up-to-date materials …
Nonlinear Acoustics - SpringerLink
Chapters 10 through 15 cover applications and additional methodologies encountered in nonlinear acoustics that include perturbation and numerical methods, ray theory for inhomogeneous …
Home | Journal of Nonlinear Science - Springer
The mission of the Journal of Nonlinear Science is to publish papers that augment the fundamental ways we describe, model, and predict nonlinear phenomena. It features papers …
Nonlinear Systems: Analysis, Stability, and Control | SpringerLink
Coupled with this set of analytic advances has been the vast increase in computational power available for both the simulation and visualization of nonlinear systems as well as for the …
Articles | Nonlinear Dynamics - Springer
4 days ago · Nonlinear Dynamics is a hybrid journal publishing original content at the forefront of nonlinear dynamic research across diverse systems and scales. The ...
Nonlinear Dynamics: A Concise Introduction Interlaced with Code ...
This concise and up-to-date textbook provides an accessible introduction to the core concepts of nonlinear dynamics as well as its existing and potential applications. The book is aimed at …
Data-driven nonlinear and stochastic dynamics with control
Dec 16, 2024 · The analysis is developed with reference to a nonlinear beam where the two boundary conditions have nonlinearities and masses, with the goal of identifying the uncertain …
Lectures on Nonlinear Dynamics - SpringerLink
This book presents a compilation of lectures delivered at the São Paulo School of Advanced Sciences on Nonlinear Dynamics, categorized into four groups: parametric resonance, …
Aims and scope | Nonlinear Dynamics - Springer
Nonlinear Dynamics provides a forum for the rapid publication of original research in the field of nonlinear dynamics. The scope of the journal encompasses all nonlinear dynamic phenomena …
