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Author : Dimitri P. Bertsekas
Publisher : MIT Press
Page : 384 pages
File Size : 50,6 Mb
Release : 1991
Category : Business & Economics
ISBN : 0262023342
Linear Network Optimization presents a thorough treatment of classical approaches to network problems such as shortest path, max-flow, assignment, transportation, and minimum cost flow problems.
Author : D Z Du,P M Pardalos
Publisher : World Scientific
Page : 416 pages
File Size : 52,6 Mb
Release : 1993-04-27
Category : Electronic
ISBN : 9789814504584
In the past few decades, there has been a large amount of work on algorithms for linear network flow problems, special classes of network problems such as assignment problems (linear and quadratic), Steiner tree problem, topology network design and nonconvex cost network flow problems. Network optimization problems find numerous applications in transportation, in communication network design, in production and inventory planning, in facilities location and allocation, and in VLSI design. The purpose of this book is to cover a spectrum of recent developments in network optimization problems, from linear networks to general nonconvex network flow problems. Contents:Greedily Solvable Transportation Networks and Edge-Guided Vertex Elimination (I Adler & R Shamir)Networks Minimizing Length Plus the Number of Steiner Points (T Colthurst et al.)Practical Experiences Using an Interactive Optimization Procedure for Vehicle Scheduling (J R Daduna et al.)Subset Interconnection Designs: Generalizations of Spanning Trees and Steiner Trees (D-Z Du & P M Pardalos)Polynomial and Strongly Polynomial Algorithms for Convex Network Optimization (D S Hochbaum)Hamiltonian Circuits for 2-Regular Interconnection Networks (F K Hwang & W-C W Li)Equivalent Formulations for the Steiner Problem in Graphs (B N Khoury et al.)Minimum Concave-Cost Network Flow Problems with a Single Nonlinear Arc Cost (B Klinz & H Tuy)A Method for Solving Network Flow Problems with General Nonlinear Arc Costs (B W Lamar)Application of Global Line Search in Optimization of Networks (J Mockus)Solving Nonlinear Programs with Embedded Network Structures (M Ç Pinar & S A Zenios)On Algorithms for Nonlinear Dynamic Networks (W B Powell et al.)Strategic and Tactical Models and Algorithms for the Coal Industry Under the 1990 Clean Air Act (H D Sherali & Q J Saifee)Multi-Objective Routing in Stochastic Evacuation Networks (J M Smith)A Simplex Method for Network Programs with Convex Separable Piecewise Linear Costs and Its Application to Stochastic Transshipment Problems (J Sun et al.)A Bibliography on Network Flow Problems (M Veldhorst)Tabu Search: Applications and Prospects (S Voß)The Shortest Path Network and Its Applications in Bicriteria Shortest Path Problems (G-L Xue & S-Z Sun)A Network Formalism for Pure Exchange Economic Equilibria (L Zhao & A Nagurney)Steiner Problem in Multistage Computer Networks (S Bhattacharya & B Dasgupta) Readership: Applied mathematicians. keywords:“This volume reflects the wide spectrum of recent research activities in the design and analysis of algorithms and the applications of networks.”Journal of Global Optimization
Author : R. Tyrell Rockafellar
Publisher : Athena Scientific
Page : 632 pages
File Size : 47,9 Mb
Release : 1999-06-01
Category : Mathematics
ISBN : 9781886529069
A rigorous and comprehensive treatment of network flow theory and monotropic optimization by one of the world's most renowned applied mathematicians. This classic textbook covers extensively the duality theory and the algorithms of linear and nonlinear network optimization optimization, and their significant extensions to monotropic programming (separable convex constrained optimization problems, including linear programs). It complements our other book on the subject of network optimization Network Optimization: Continuous and Discrete Models (Athena Scientific, 1998). Monotropic programming problems are characterized by a rich interplay between combinatorial structure and convexity properties. Rockafellar develops, for the first time, algorithms and a remarkably complete duality theory for these problems. Among its special features the book: (a) Treats in-depth the duality theory for linear and nonlinear network optimization (b) Uses a rigorous step-by-step approach to develop the principal network optimization algorithms (c) Covers the main algorithms for specialized network problems, such as max-flow, feasibility, assignment, and shortest path (d) Develops in detail the theory of monotropic programming, based on the author's highly acclaimed research (e) Contains many examples, illustrations, and exercises (f) Contains much new material not found in any other textbook
Author : Dimitri Bertsekas
Publisher : Athena Scientific
Page : 607 pages
File Size : 42,9 Mb
Release : 1998-01-01
Category : Business & Economics
ISBN : 9781886529021
An insightful, comprehensive, and up-to-date treatment of linear, nonlinear, and discrete/combinatorial network optimization problems, their applications, and their analytical and algorithmic methodology. It covers extensively theory, algorithms, and applications, and it aims to bridge the gap between linear and nonlinear network optimization on one hand, and integer/combinatorial network optimization on the other. It complements several of our books: Convex Optimization Theory (Athena Scientific, 2009), Convex Optimization Algorithms (Athena Scientific, 2015), Introduction to Linear Optimization (Athena Scientific, 1997), Nonlinear Programming (Athena Scientific, 1999), as well as our other book on the subject of network optimization Network Flows and Monotropic Optimization (Athena Scientific, 1998).
Author : Richard Kipp Martin
Publisher : Springer Science & Business Media
Page : 739 pages
File Size : 48,7 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9781461549758
This is a textbook about linear and integer linear optimization. There is a growing need in industries such as airline, trucking, and financial engineering to solve very large linear and integer linear optimization problems. Building these models requires uniquely trained individuals. Not only must they have a thorough understanding of the theory behind mathematical programming, they must have substantial knowledge of how to solve very large models in today's computing environment. The major goal of the book is to develop the theory of linear and integer linear optimization in a unified manner and then demonstrate how to use this theory in a modern computing environment to solve very large real world problems. After presenting introductory material in Part I, Part II of this book is de voted to the theory of linear and integer linear optimization. This theory is developed using two simple, but unifying ideas: projection and inverse projec tion. Through projection we take a system of linear inequalities and replace some of the variables with additional linear inequalities. Inverse projection, the dual of this process, involves replacing linear inequalities with additional variables. Fundamental results such as weak and strong duality, theorems of the alternative, complementary slackness, sensitivity analysis, finite basis the orems, etc. are all explained using projection or inverse projection. Indeed, a unique feature of this book is that these fundamental results are developed and explained before the simplex and interior point algorithms are presented.
Author : Glenn Hurlbert
Publisher : Springer Science & Business Media
Page : 279 pages
File Size : 45,5 Mb
Release : 2009-11-09
Category : Mathematics
ISBN : 9780387791487
The Subject A little explanation is in order for our choice of the title Linear Opti- 1 mization (and corresponding terminology) for what has traditionally been called Linear Programming.Theword programming in this context can be confusing and/or misleading to students. Linear programming problems are referred to as optimization problems but the general term linear p- gramming remains. This can cause people unfamiliar with the subject to think that it is about programming in the sense of writing computer code. It isn’t. This workbook is about the beautiful mathematics underlying the ideas of optimizing linear functions subject to linear constraints and the algorithms to solve such problems. In particular, much of what we d- cuss is the mathematics of Simplex Algorithm for solving such problems, developed by George Dantzig in the late 1940s. The word program in linear programming is a historical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencetheterm.
Author : Xiang-Sun Zhang
Publisher : Springer Science & Business Media
Page : 369 pages
File Size : 53,8 Mb
Release : 2013-03-09
Category : Science
ISBN : 9781475731675
People are facing more and more NP-complete or NP-hard problems of a combinatorial nature and of a continuous nature in economic, military and management practice. There are two ways in which one can enhance the efficiency of searching for the solutions of these problems. The first is to improve the speed and memory capacity of hardware. We all have witnessed the computer industry's amazing achievements with hardware and software developments over the last twenty years. On one hand many computers, bought only a few years ago, are being sent to elementary schools for children to learn the ABC's of computing. On the other hand, with economic, scientific and military developments, it seems that the increase of intricacy and the size of newly arising problems have no end. We all realize then that the second way, to design good algorithms, will definitely compensate for the hardware limitations in the case of complicated problems. It is the collective and parallel computation property of artificial neural net works that has activated the enthusiasm of researchers in the field of computer science and applied mathematics. It is hard to say that artificial neural networks are solvers of the above-mentioned dilemma, but at least they throw some new light on the difficulties we face. We not only anticipate that there will be neural computers with intelligence but we also believe that the research results of artificial neural networks might lead to new algorithms on von Neumann's computers.
Author : H.A. Eiselt,Carl-Louis Sandblom
Publisher : Springer Science & Business Media
Page : 501 pages
File Size : 48,5 Mb
Release : 2013-03-14
Category : Business & Economics
ISBN : 9783662041970
The purpose of this book is to provide readers with an introduction to the very active field of integer programming and network models. The idea is to cover the main parts of the field without being too detailed or too technical. As a matter of fact, we found it somewhat surprising that most--especially newer---books are strongly algorithmically oriented. In contrast, the main emphasis of this book is on models rather than methods. This focus expresses our view that methods are tools to solve actual problems and not ends in themselves. As such, graduate (and with some omissions, undergraduate) students may find this book helpful in their studies as will practitioners who would like to get acquainted with a field or use this text as a refresher. This premise has resulted in a coverage that omits material that is standard fare in other books, whereas it covers topics that are only infrequently found elsewhere. There are some, yet relatively few, prerequisites for the reader. Most material that is required for the understanding of more than one chapter is presented in one of the four chapters of the introductory part, which reviews the main results in linear programming, the analysis of algorithms, graphs and networks, and dynamic programming, respectively. Readers who are familiar with the issues involved can safely skip that part. The three main parts of the book rely on intuitive reasoning and examples, whenever practical, instead of theorems and proofs.
Author : Panos M. Pardalos,Donald W. Hearn,William W. Hager
Publisher : Springer Science & Business Media
Page : 495 pages
File Size : 55,5 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642591792
Network optimization is important in the modeling of problems and processes from such fields as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Recent advances in data structures, computer technology, and algorithm development have made it possible to solve classes of network optimization problems that until recently were intractable. The refereed papers in this volume reflect the interdisciplinary efforts of a large group of scientists from academia and industry to model and solve complicated large-scale network optimization problems.
Author : Dimitris Bertsimas,John N. Tsitsiklis
Publisher : Unknown
Page : 587 pages
File Size : 45,7 Mb
Release : 1997-01-01
Category : Mathematics
ISBN : 1886529191
Author : Gerard Sierksma,Yori Zwols
Publisher : CRC Press
Page : 676 pages
File Size : 43,6 Mb
Release : 2015-05-01
Category : Business & Economics
ISBN : 9781498743129
Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig's simplex algorithm, duality, sensitivity analysis, integer optimization models
Author : David J. Rader
Publisher : John Wiley & Sons
Page : 631 pages
File Size : 55,8 Mb
Release : 2013-06-07
Category : Mathematics
ISBN : 9781118627358
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations research: modeling real-world problems as linear optimization problem; designing the necessary algorithms to solve these problems; and using mathematical theory to justify algorithmic development. Treating real-world examples as mathematical problems, the author begins with an introduction to operations research and optimization modeling that includes applications form sports scheduling an the airline industry. Subsequent chapters discuss algorithm design for continuous linear optimization problems, covering topics such as convexity. Farkas’ Lemma, and the study of polyhedral before culminating in a discussion of the Simplex Method. The book also addresses linear programming duality theory and its use in algorithm design as well as the Dual Simplex Method. Dantzig-Wolfe decomposition, and a primal-dual interior point algorithm. The final chapters present network optimization and integer programming problems, highlighting various specialized topics including label-correcting algorithms for the shortest path problem, preprocessing and probing in integer programming, lifting of valid inequalities, and branch and cut algorithms. Concepts and approaches are introduced by outlining examples that demonstrate and motivate theoretical concepts. The accessible presentation of advanced ideas makes core aspects easy to understand and encourages readers to understand how to think about the problem, not just what to think. Relevant historical summaries can be found throughout the book, and each chapter is designed as the continuation of the “story” of how to both model and solve optimization problems by using the specific problems-linear and integer programs-as guides. The book’s various examples are accompanied by the appropriate models and calculations, and a related Web site features these models along with MapleTM and MATLAB® content for the discussed calculations. Thoroughly class-tested to ensure a straightforward, hands-on approach, Deterministic Operations Research is an excellent book for operations research of linear optimization courses at the upper-undergraduate and graduate levels. It also serves as an insightful reference for individuals working in the fields of mathematics, engineering, computer science, and operations research who use and design algorithms to solve problem in their everyday work.
Author : Horst W. Hamacher,Kathrin Klamroth
Publisher : Unknown
Page : 250 pages
File Size : 51,7 Mb
Release : 2000
Category : Linear programming
ISBN : CORNELL:31924095791103
Ziel des Buches ist es, Grundlagen der Linearen Optimierung einzuführen und einige der klassischen polynomial lösbaren Netzwerkprobleme vorzustellen. Das Besondere dieses Lehrbuches ist die Tatsache, dass die Textteile parallel auf Deutsch und Englisch formuliert wurden, so dass neben der Vermittlung des Grundwissens in mathematischer Optimierung auch eine Einführung ins Fachenglisch bzw. in die deutsche Sprache stattfindet. The book is geared towards a basic understanding of the concepts of linear optimization and of some classic, polynomially solvable network optimization problems. The unique feature of this book is that the verbal parts have been formulated both in German and English. In this way teaching of basic knowledge in mathematical optimization can be combined with an introduction into English as technical language or into the German language.
Author : Craig A. Tovey
Publisher : CRC Press
Page : 587 pages
File Size : 54,5 Mb
Release : 2020-12-15
Category : Business & Economics
ISBN : 9781439887479
Linear Optimization and Dualiyy: A Modern Exposition departs from convention in significant ways. Standard linear programming textbooks present the material in the order in which it was discovered. Duality is treated as a difficult add-on after coverage of formulation, the simplex method, and polyhedral theory. Students end up without knowing duality in their bones. This text brings in duality in Chapter 1 and carries duality all the way through the exposition. Chapter 1 gives a general definition of duality that shows the dual aspects of a matrix as a column of rows and a row of columns. The proof of weak duality in Chapter 2 is shown via the Lagrangian, which relies on matrix duality. The first three LP formulation examples in Chapter 3 are classic primal-dual pairs including the diet problem and 2-person zero sum games. For many engineering students, optimization is their first immersion in rigorous mathematics. Conventional texts assume a level of mathematical sophistication they don’t have. This text embeds dozens of reading tips and hundreds of answered questions to guide such students. Features Emphasis on duality throughout Practical tips for modeling and computation Coverage of computational complexity and data structures Exercises and problems based on the learning theory concept of the zone of proximal development Guidance for the mathematically unsophisticated reader About the Author Craig A. Tovey is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. Dr. Tovey received an AB from Harvard College, an MS in computer science and a PhD in operations research from Stanford University. His principal activities are in operations research and its interdisciplinary applications. He received a Presidential Young Investigator Award and the Jacob Wolfowitz Prize for research in heuristics. He was named an Institute Fellow at Georgia Tech, and was recognized by the ACM Special Interest Group on Electronic Commerce with the Test of Time Award. Dr. Tovey received the 2016 Golden Goose Award for his research on bee foraging behavior leading to the development of the Honey Bee Algorithm.
Author : Robert J Vanderbei
Publisher : Springer Science & Business Media
Page : 414 pages
File Size : 41,6 Mb
Release : 2013-07-16
Category : Business & Economics
ISBN : 9781461476306
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.
