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Practical Linear Programming Under Uncertainty
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Book Synopsis Practical Linear Programming Under Uncertainty by : Cesar Beltran-Royo
Download or read book Practical Linear Programming Under Uncertainty written by Cesar Beltran-Royo and published by Createspace Independent Publishing Platform. This book was released on 2017-09-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Note: You can "look inside" this book at Amazon.com. As is well known, there are many benefits of Linear Programming. As an optimization tool it is useful for decision making in order to increase profit or decrease cost. The number of applications is very large: finance, airline industry, energy production, logistics, telecommunications, advertising industry, etc. This manual is a simple introduction to Stochastic Linear Programming. It is intended for practitioners in business, engineering and industry who already use deterministic Linear Programming and wish to improve their results by taking into account the parameter uncertainty in an effective way. It is also suitable as an intuitive introduction to Stochastic Linear Programming for graduate courses. Cesar Beltran-Royo is a Professor of Statistics and Operations Research at King Juan Carlos University, Madrid, Spain.
Book Synopsis Methods of Solution of Linear Programs Under Uncertainty by : Albert Madansky
Download or read book Methods of Solution of Linear Programs Under Uncertainty written by Albert Madansky and published by . This book was released on 1960 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three most usual methods of reducing the effects of uncertainty in the technology matrix, requirement vector, or cost vector of a linear programming problem are the expected-value solution, the 'fat' solution, and the 'slack' solution. These methods are explained in some detail, and the relation between these various methods is pointed out. (Author).
Book Synopsis Stochastic Programming by : Willem K. Klein Haneveld
Download or read book Stochastic Programming written by Willem K. Klein Haneveld and published by Springer Nature. This book was released on 2019-10-24 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book’s closing section, several case studies are presented, helping students apply the theory covered to practical problems. The book is based on lecture notes developed for an Econometrics and Operations Research course for master students at the University of Groningen, the Netherlands - the longest-standing Stochastic Programming course worldwide.
Book Synopsis Stochastic Linear Programming by : P. Kall
Download or read book Stochastic Linear Programming written by P. Kall and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: Todaymanyeconomists, engineers and mathematicians are familiar with linear programming and are able to apply it. This is owing to the following facts: during the last 25 years efficient methods have been developed; at the same time sufficient computer capacity became available; finally, in many different fields, linear programs have turned out to be appropriate models for solving practical problems. However, to apply the theory and the methods of linear programming, it is required that the data determining a linear program be fixed known numbers. This condition is not fulfilled in many practical situations, e. g. when the data are demands, technological coefficients, available capacities, cost rates and so on. It may happen that such data are random variables. In this case, it seems to be common practice to replace these random variables by their mean values and solve the resulting linear program. By 1960 various authors had already recog nized that this approach is unsound: between 1955 and 1960 there were such papers as "Linear Programming under Uncertainty", "Stochastic Linear Pro gramming with Applications to Agricultural Economics", "Chance Constrained Programming", "Inequalities for Stochastic Linear Programming Problems" and "An Approach to Linear Programming under Uncertainty".
Book Synopsis Linear Programming for Financial Planning Under Uncertainty (Classic Reprint) by : Stewart C. Myers
Download or read book Linear Programming for Financial Planning Under Uncertainty (Classic Reprint) written by Stewart C. Myers and published by Forgotten Books. This book was released on 2019-02-16 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Linear Programming for Financial Planning Under Uncertainty LP problems, should generate interest in the models as practical decision-making tools. It is too soon, of course, to assess their ultimate fruitfulness in either respect. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Book Synopsis Linear Programming Under Uncertainty by : Juergen H. Eufinger
Download or read book Linear Programming Under Uncertainty written by Juergen H. Eufinger and published by . This book was released on 1966 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Some Approaches to Linear Programming Under Uncertainty by : Gary Grove Koch
Download or read book Some Approaches to Linear Programming Under Uncertainty written by Gary Grove Koch and published by . This book was released on 1963 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Practical Linear Programming by : David J. Pannell
Download or read book Introduction to Practical Linear Programming written by David J. Pannell and published by Wiley-Interscience. This book was released on 1997 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, nonmathematical guide to the practical application of linear programming models—for students and professionals in any field From finding the least-cost method for manufacturing a given product to determining the most profitable use for a given resource, there are countless practical applications for linear programming models. This self-contained book and disk set provides everything you need to know to apply linear programming to real-world situations—how to prepare input, how to interpret output, what to do if the model will not solve, and how to make your results useful and usable—while entrusting the hard-core arithmetic to the user-friendly computer package on disk. Written in clear prose that stays away from the complex mathematics underlying the technique, Introduction to Practical Linear Programming contains: A complete introduction to problem structure, assumptions, applications, and other core concepts A detailed, step-by-step guide to model construction (from a problem description to a useful model) and interpretation of output Linear programming examples and exercises from a range of real-life areas, including agriculture, manufacturing, finance, and advertising Important techniques for troubleshooting and error identification Procedures for testing how good your model is—how robust are the results?—and more System.
Book Synopsis Linear Programming Under Uncertainty .... by : George B. Dantzig
Download or read book Linear Programming Under Uncertainty .... written by George B. Dantzig and published by . This book was released on 1955 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete computation procedure is given for a special class of two-stage linear programming models in which allocations in the first stage are made to meet an uncertain but known distribution of demands occurring in the second stage. This case, applicable to many practical problems constitutes the principal part of the paper. Next, a class of models is considered where the activities are divided into two or more stages. The quantities of activities in the first stage are the only ones that can be determined in advance because those in the second and latter stages depend on the outcome of random events. Theorems on convexity of the objective (cost) functions are established for the general m-stage case. (Author).
Book Synopsis Linear Programming for Financial Planning Under Uncertainty by : Stewart C. Myers
Download or read book Linear Programming for Financial Planning Under Uncertainty written by Stewart C. Myers and published by Forgotten Books. This book was released on 2015-06-17 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Linear Programming for Financial Planning Under Uncertainty 2. The models yield simultaneous solutions for the firm's optimal financing and investment decisions. The financing decision is not considered "with the investment decision given," nor vice-versa. 3. Some practical difficulties associated with the cost of capital concept are avoided. The traditional weighted average cost of capital does not appear in these LP models. The first two characteristics should lead to some interest in the mosels as theory; the third, along with the ease of solution of LP problems, should generate interest in the models as practical decision-making tools. However, this paper does not include a detailed model for practical application. The paper is organized as follows. The general linear format is explained in the next section. The key assumption justifying it is that the structure of security prices at equilibrium is best described by the class of security valuation models which imply risk-independence of financing and investment options. The following section examines a simple model in detail, and contrasts the LP approach with "traditional" approaches using the cost of capital. Practical implications of the model are discussed in the third section. We will consider the firm's financial planning problem in the following terms. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Book Synopsis Robust Optimization by : Aharon Ben-Tal
Download or read book Robust Optimization written by Aharon Ben-Tal and published by Princeton University Press. This book was released on 2009-08-10 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
Book Synopsis An Introduction to Fuzzy Linear Programming Problems by : Jagdeep Kaur
Download or read book An Introduction to Fuzzy Linear Programming Problems written by Jagdeep Kaur and published by Springer. This book was released on 2016-04-02 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a snapshot of the state of the art in the field of fully fuzzy linear programming. The main focus is on showing current methods for finding the fuzzy optimal solution of fully fuzzy linear programming problems in which all the parameters and decision variables are represented by non-negative fuzzy numbers. It presents new methods developed by the authors, as well as existing methods developed by others, and their application to real-world problems, including fuzzy transportation problems. Moreover, it compares the outcomes of the different methods and discusses their advantages/disadvantages. As the first work to collect at one place the most important methods for solving fuzzy linear programming problems, the book represents a useful reference guide for students and researchers, providing them with the necessary theoretical and practical knowledge to deal with linear programming problems under uncertainty.
Book Synopsis The Practical Use of Linear Programming in Farm Planning, Involving Problems of Flexibility and Uncertainty in Seasonal Labour Inputs by : A. M. M. McFarquhar
Download or read book The Practical Use of Linear Programming in Farm Planning, Involving Problems of Flexibility and Uncertainty in Seasonal Labour Inputs written by A. M. M. McFarquhar and published by . This book was released on 19?? with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Programming Under Uncertainty with Discrete D.f by : Mostafa El-Agizy
Download or read book Programming Under Uncertainty with Discrete D.f written by Mostafa El-Agizy and published by . This book was released on 1964 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many realistic situations can be represented by the two-stage linear programming problem under uncertainty. Two special cases, that fit in this formulation, are discussed to expose their interesting features: (1) a transportation problem (2) a production-inventory problem. Many other examples are available in the literature. For the stochastic transportation problem it is shown that the corresponding deterministic equivalent program represents a directed network. For the production-inventory problem, since the matrix B = I, the demand constraints disappear in the equivalent program, thus the number of constraints is reduced to a minimum; namely, the fixed constraints.
Book Synopsis Linear Programming by : Robert J Vanderbei
Download or read book Linear Programming written by Robert J Vanderbei and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Third Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. You’ll discover a host of practical business applications as well as non-business applications. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered. The book’s accompanying website includes the C programs, JAVA tools, and new online instructional tools and exercises.
Book Synopsis Notes on Linear Programming by : George Bernard Dantzig
Download or read book Notes on Linear Programming written by George Bernard Dantzig and published by . This book was released on 1954 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Combinatorial Optimization Under Uncertainty by : Ritu Arora
Download or read book Combinatorial Optimization Under Uncertainty written by Ritu Arora and published by CRC Press. This book was released on 2023-05-12 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the basic ideas, underlying principles, mathematical formulations, analysis and applications of the different combinatorial problems under uncertainty and attempts to provide solutions for the same. Uncertainty influences the behaviour of the market to a great extent. Global pandemics and calamities are other factors which affect and augment unpredictability in the market. The intent of this book is to develop mathematical structures for different aspects of allocation problems depicting real life scenarios. The novel methods which are incorporated in practical scenarios under uncertain circumstances include the STAR heuristic approach, Matrix geometric method, Ranking function and Pythagorean fuzzy numbers, to name a few. Distinct problems which are considered in this book under uncertainty include scheduling, cyclic bottleneck assignment problem, bilevel transportation problem, multi-index transportation problem, retrial queuing, uncertain matrix games, optimal production evaluation of cotton in different soil and water conditions, the healthcare sector, intuitionistic fuzzy quadratic programming problem, and multi-objective optimization problem. This book may serve as a valuable reference for researchers working in the domain of optimization for solving combinatorial problems under uncertainty. The contributions of this book may further help to explore new avenues leading toward multidisciplinary research discussions.
