Linear And Integer Optimization
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| Author | : Richard Kipp Martin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 739 |
| Release | : 2012-12-06 |
| Genre | : Business & Economics |
| ISBN | : 1461549752 |
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 | : Gerard Sierksma |
| Publisher | : CRC Press |
| Total Pages | : 676 |
| Release | : 2015-05-01 |
| Genre | : Business & Economics |
| ISBN | : 1498743129 |
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 | : Alexander Schrijver |
| Publisher | : John Wiley & Sons |
| Total Pages | : 488 |
| Release | : 1998-06-11 |
| Genre | : Mathematics |
| ISBN | : 9780471982326 |
Theory of Linear and Integer Programming Alexander Schrijver Centrum voor Wiskunde en Informatica, Amsterdam, The Netherlands This book describes the theory of linear and integer programming and surveys the algorithms for linear and integer programming problems, focusing on complexity analysis. It aims at complementing the more practically oriented books in this field. A special feature is the author's coverage of important recent developments in linear and integer programming. Applications to combinatorial optimization are given, and the author also includes extensive historical surveys and bibliographies. The book is intended for graduate students and researchers in operations research, mathematics and computer science. It will also be of interest to mathematical historians. Contents 1 Introduction and preliminaries; 2 Problems, algorithms, and complexity; 3 Linear algebra and complexity; 4 Theory of lattices and linear diophantine equations; 5 Algorithms for linear diophantine equations; 6 Diophantine approximation and basis reduction; 7 Fundamental concepts and results on polyhedra, linear inequalities, and linear programming; 8 The structure of polyhedra; 9 Polarity, and blocking and anti-blocking polyhedra; 10 Sizes and the theoretical complexity of linear inequalities and linear programming; 11 The simplex method; 12 Primal-dual, elimination, and relaxation methods; 13 Khachiyan's method for linear programming; 14 The ellipsoid method for polyhedra more generally; 15 Further polynomiality results in linear programming; 16 Introduction to integer linear programming; 17 Estimates in integer linear programming; 18 The complexity of integer linear programming; 19 Totally unimodular matrices: fundamental properties and examples; 20 Recognizing total unimodularity; 21 Further theory related to total unimodularity; 22 Integral polyhedra and total dual integrality; 23 Cutting planes; 24 Further methods in integer linear programming; Historical and further notes on integer linear programming; References; Notation index; Author index; Subject index
| Author | : Michele Conforti |
| Publisher | : Springer |
| Total Pages | : 466 |
| Release | : 2014-11-15 |
| Genre | : Business & Economics |
| ISBN | : 331911008X |
This book is an elegant and rigorous presentation of integer programming, exposing the subject’s mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory. Each chapter is accompanied by an expertly informed guide to the literature and special topics, rounding out the reader’s understanding and serving as a gateway to deeper study. Key topics include: formulations polyhedral theory cutting planes decomposition enumeration semidefinite relaxations Written by renowned experts in integer programming and combinatorial optimization, Integer Programming is destined to become an essential text in the field.
| Author | : T. C. Hu |
| Publisher | : Springer |
| Total Pages | : 151 |
| Release | : 2016-05-03 |
| Genre | : Technology & Engineering |
| ISBN | : 3319240013 |
This textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc., are becoming fundamental toolkits for data and information science and technology. The authors’ approach is accessible to students from almost all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification and computer vision. The presentations enables the basis for numerous approaches to solving hard combinatorial optimization problems through randomization and approximation. Readers will learn to cast various problems that may arise in their research as optimization problems, understand the cases where the optimization problem will be linear, choose appropriate solution methods and interpret results appropriately.
| Author | : Jean-Bernard Lasserre |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 167 |
| Release | : 2009-04-21 |
| Genre | : Business & Economics |
| ISBN | : 0387094148 |
This book analyzes and compares four closely related problems, namely linear programming, integer programming, linear integration, and linear summation (or counting). The book provides some new insights on duality concepts for integer programs.
| Author | : Carlos Henggeler Antunes |
| Publisher | : Springer |
| Total Pages | : 216 |
| Release | : 2016-04-08 |
| Genre | : Business & Economics |
| ISBN | : 331928746X |
This book opens the door to multiobjective optimization for students in fields such as engineering, management, economics and applied mathematics. It offers a comprehensive introduction to multiobjective optimization, with a primary emphasis on multiobjective linear programming and multiobjective integer/mixed integer programming. A didactic book, it is mainly intended for undergraduate and graduate students, but can also be useful for researchers and practitioners. Further, it is accompanied by an interactive software package - developed by the authors for Windows platforms - which can be used for teaching and decision-making support purposes in multiobjective linear programming problems. Thus, besides the textbook’s coverage of the essential concepts, theory and methods, complemented with illustrative examples and exercises, the computational tool enables students to experiment and enhance their technical skills, as well as to capture the essential characteristics of real-world problems.
| Author | : Gerard Sierksma |
| Publisher | : CRC Press |
| Total Pages | : 704 |
| Release | : 1996 |
| Genre | : Business & Economics |
| ISBN | : |
This unique reference/text details the theoretical and practical aspects of linear and integer programming - covering a wide range of subjects, including duality, optimality criteria, sensitivity analysis, and numerous solution techniques for linear programming problems. Requiring only an elementary knowledge of set theory, trigonometry, and calculus, Linear and Integer Programming reflects both the problem-analyzing and problem-solving abilities of linear and integer programming ... presents the more rigorous mathematical material in such a way that it can be easily skipped without disturbing the readability of the text ... contains important pedagogical features such as a user-friendly, IBM-compatible computer software package for solving linear-programming problems, numerous case studies, fully worked examples, helpful end-of-chapter exercises, the answers to selected problems, key literature citations, and over 1375 equations, drawings, and tables ... and more. Linear and Integer programming is a fundamental reference for applied mathematicians, operations researchers, computer scientists, economists, and industrial engineers, as well as an ideal text for upper-level undergraduate and graduate students in this disciplines.
| Author | : Dan Gusfield |
| Publisher | : Cambridge University Press |
| Total Pages | : 431 |
| Release | : 2019-06-13 |
| Genre | : Computers |
| ISBN | : 1108421768 |
This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.
| Author | : Renata Mansini |
| Publisher | : Springer |
| Total Pages | : 131 |
| Release | : 2015-06-10 |
| Genre | : Business & Economics |
| ISBN | : 3319184822 |
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
