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On the Feasibility of a Generalized Linear Program

On the Feasibility of a Generalized Linear Program
Author: Hu Hui
Publisher:
Total Pages: 26
Release: 1989
Genre: Linear programming
ISBN:

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Abstract: "The first algorithm for solving generalized linear programs was given by George B. Dantzig. His algorithm assumes that a basic feasible solution of the generalized linear program to be solved exists and is given. If the initial basic feasible solution is non-degenerate, then his algorithm is guaranteed to converge. The purpose of this paper is to show how to find an initial basic feasible (possibly degenerate) solution of a generalized linear program by applying the same algorithm to a 'phase-one' problem without requiring that the initial basic feasible solution to the latter be non-degenerate."


Feasibility and Infeasibility in Optimization:

Feasibility and Infeasibility in Optimization:
Author: John W. Chinneck
Publisher: Springer Science & Business Media
Total Pages: 283
Release: 2007-10-25
Genre: Mathematics
ISBN: 0387749322

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Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.


Linear Programs and Related Problems

Linear Programs and Related Problems
Author: Evar D. Nering
Publisher: Academic Press
Total Pages: 618
Release: 1993
Genre: Computers
ISBN: 9780125154406

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This text is concerned primarily with the theory of linear and nonlinear programming, and a number of closely-related problems, and with algorithms appropriate to those problems. In the first part of the book, the authors introduce the concept of duality which serves as a unifying concept throughout the book. The simplex algorithm is presented along with modifications and adaptations to problems with special structures. Two alternative algorithms, the ellipsoidal algorithm and Karmarker's algorithm, are also discussed, along with numerical considerations. the second part of the book looks at specific types of problems and methods for their solution. This book is designed as a textbook for mathematical programming courses, and each chapter contains numerous exercises and examples.


Linear Programming 2

Linear Programming 2
Author: George B. Dantzig
Publisher: Springer Science & Business Media
Total Pages: 461
Release: 2006-04-28
Genre: Mathematics
ISBN: 0387215697

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George Dantzig is widely regarded as the founder of this subject with his invention of the simplex algorithm in the 1940's. In this second volume, the theory of the items discussed in the first volume is expanded to include such additional advanced topics as variants of the simplex method; interior point methods, GUB, decomposition, integer programming, and game theory. Graduate students in the fields of operations research, industrial engineering and applied mathematics will thus find this volume of particular interest.


Cities and Their Vital Systems

Cities and Their Vital Systems
Author: Advisory Committee on Technology and Society
Publisher: National Academies Press
Total Pages: 1298
Release: 1989
Genre: Social Science
ISBN: 9780309037860

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Cities and Their Vital Systems asks basic questions about the longevity, utility, and nature of urban infrastructures; analyzes how they grow, interact, and change; and asks how, when, and at what cost they should be replaced. Among the topics discussed are problems arising from increasing air travel and airport congestion; the adequacy of water supplies and waste treatment; the impact of new technologies on construction; urban real estate values; and the field of "telematics," the combination of computers and telecommunications that makes money machines and national newspapers possible.


The Design of Approximation Algorithms

The Design of Approximation Algorithms
Author: David P. Williamson
Publisher: Cambridge University Press
Total Pages: 517
Release: 2011-04-26
Genre: Computers
ISBN: 1139498177

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Discrete optimization problems are everywhere, from traditional operations research planning (scheduling, facility location and network design); to computer science databases; to advertising issues in viral marketing. Yet most such problems are NP-hard; unless P = NP, there are no efficient algorithms to find optimal solutions. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first section is devoted to a single algorithmic technique applied to several different problems, with more sophisticated treatment in the second section. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithm courses, it will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.


Colourful Linear Programming Feasibility Problem

Colourful Linear Programming Feasibility Problem
Author: Guohong Rong
Publisher: LAP Lambert Academic Publishing
Total Pages: 80
Release: 2012
Genre:
ISBN: 9783659286773

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This problem was presented by Barany and Onn in 1997 and it is still not known if a polynomial-time algorithm for the problem exists. The monochrome version of this problem, expressing p as a convex combination of points in a set S, is a traditional linear programming feasibility problem. The colourful Caratheodory Theorem, due to Barany in 1982, provides a sufficient condition for the existence of a colourful set of points containing p in its convex hull. Barany's result was generalized by Holmsen et al. in 2008 and by Arocha et al. in 2009 before being recently further generalized by Meunier and Deza. We study algorithms for colourful linear programming under the conditions of Barany and their generalizations. In particular, we implement the Meunier-Deza algorithm and enhance previously used random case generators. Computational benchmarking and a performance analysis including a comparison between the two algorithms of Barany and Onn and the one of Meunier and Deza, and random picking are presented.


Linear Programming 1

Linear Programming 1
Author: George B. Dantzig
Publisher: Springer Science & Business Media
Total Pages: 462
Release: 2006-04-06
Genre: Business & Economics
ISBN: 0387226338

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Encompassing all the major topics students will encounter in courses on the subject, the authors teach both the underlying mathematical foundations and how these ideas are implemented in practice. They illustrate all the concepts with both worked examples and plenty of exercises, and, in addition, provide software so that students can try out numerical methods and so hone their skills in interpreting the results. As a result, this will make an ideal textbook for all those coming to the subject for the first time. Authors' note: A problem recently found with the software is due to a bug in Formula One, the third party commercial software package that was used for the development of the interface. It occurs when the date, currency, etc. format is set to a non-United States version. Please try setting your computer date/currency option to the United States option . The new version of Formula One, when ready, will be posted on WWW.


Synergies of Soft Computing and Statistics for Intelligent Data Analysis

Synergies of Soft Computing and Statistics for Intelligent Data Analysis
Author: Rudolf Kruse
Publisher: Springer Science & Business Media
Total Pages: 555
Release: 2012-09-13
Genre: Technology & Engineering
ISBN: 3642330428

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In recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only present in the form of randomness --- various types of incomplete or subjective information have to be handled. About twelve years ago the idea of strengthening the dialogue between the various research communities in the field of data analysis was born and resulted in the International Conference Series on Soft Methods in Probability and Statistics (SMPS). This book gathers contributions presented at the SMPS'2012 held in Konstanz, Germany. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.