Uncertain Programming

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Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 272 pages
Book Rating : 4.30/5 ( download)

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Book Synopsis Uncertain Programming by : Baoding Liu

Download or read book Uncertain Programming written by Baoding Liu and published by Wiley-Interscience. This book was released on 1999 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, authoritative, comprehensive look at optimization theory in uncertain environments Real-life management decisions, such as buy/sell decisions in the stock market, are almost always made in uncertain environments. Is it possible to make model decision problems to fit these circumstances? Once constructed, can these models be solved? In Uncertain Programming, Baoding Liu answers both of these questions in the affirmative and goes on to lay a solid foundation for optimization in generally uncertain environments. Uncertain Programming describes the basic concepts of mathematical programming, provides a genetic algorithm for optimization problems, and introduces the techniques of stochastic and fuzzy simulation. After examining some basic results of expected value models, the book moves on to explore chance-constrained programming with stochastic parameters and illustrate applications of chance-constrained programming models. Dr. Liu discusses dependent-chance programming in stochastic environments and extends both chance-constrained and dependent-chance programming from stochastic to fuzzy environments. He then constructs a theoretical framework for fuzzy programming with fuzzy rather than crisp decisions. This remarkable and revolutionary book: * Lays a foundation for optimization theory in uncertain environments * Provides a unifying principle for dealing with stochastic and fuzzy programming * Incorporates the most recent developments in the field * Emphasizes modeling ideas, evolutionary computation, and applications of uncertain programming Uncertain Programming is a reliable, authoritative, and eye-opening guide for researchers and engineers in operations research, management science, business management, information and systems science, and computer science.

Theory and Practice of Uncertain Programming

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Author :
Publisher : Springer
ISBN 13 : 3540894845
Total Pages : 205 pages
Book Rating : 4.41/5 ( download)

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Book Synopsis Theory and Practice of Uncertain Programming by : Baoding Liu

Download or read book Theory and Practice of Uncertain Programming written by Baoding Liu and published by Springer. This book was released on 2008-12-28 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-life decisions are usually made in the state of uncertainty such as randomness and fuzziness. How do we model optimization problems in uncertain environments? How do we solve these models? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem. Researchers, practitioners and students in operations research, management science, information science, system science, and engineering will find this work a stimulating and useful reference.

Theory and Practice of Uncertain Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 3540894837
Total Pages : 205 pages
Book Rating : 4.34/5 ( download)

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Book Synopsis Theory and Practice of Uncertain Programming by : Baoding Liu

Download or read book Theory and Practice of Uncertain Programming written by Baoding Liu and published by Springer Science & Business Media. This book was released on 2009-03-17 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, vehicle routing problem, and machine scheduling problem.

Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty

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Publisher : Springer Science & Business Media
ISBN 13 : 940092111X
Total Pages : 425 pages
Book Rating : 4.15/5 ( download)

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Book Synopsis Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty by : Shi-Yu Huang

Download or read book Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty written by Shi-Yu Huang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations Research is a field whose major contribution has been to propose a rigorous fonnulation of often ill-defmed problems pertaining to the organization or the design of large scale systems, such as resource allocation problems, scheduling and the like. While this effort did help a lot in understanding the nature of these problems, the mathematical models have proved only partially satisfactory due to the difficulty in gathering precise data, and in formulating objective functions that reflect the multi-faceted notion of optimal solution according to human experts. In this respect linear programming is a typical example of impressive achievement of Operations Research, that in its detenninistic fonn is not always adapted to real world decision-making : everything must be expressed in tenns of linear constraints ; yet the coefficients that appear in these constraints may not be so well-defined, either because their value depends upon other parameters (not accounted for in the model) or because they cannot be precisely assessed, and only qualitative estimates of these coefficients are available. Similarly the best solution to a linear programming problem may be more a matter of compromise between various criteria rather than just minimizing or maximizing a linear objective function. Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.

Uncertain Graph and Network Optimization

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Author :
Publisher : Springer Nature
ISBN 13 : 9811914729
Total Pages : 144 pages
Book Rating : 4.20/5 ( download)

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Book Synopsis Uncertain Graph and Network Optimization by : Bo Zhang

Download or read book Uncertain Graph and Network Optimization written by Bo Zhang and published by Springer Nature. This book was released on 2022-05-03 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first book focuses on uncertain graph and network optimization. It covers three different main contents: uncertain graph, uncertain programming and uncertain network optimization. It also presents applications of uncertain network optimization in a lot of real problems such as transportation problems, dispatching medical supplies problems and location problems. The book is suitable for researchers, engineers, teachers and students in the field of mathematics, information science, computer science, decision science, management science and engineering, artificial intelligence, industrial engineering, economics and operations research.

Theory and Practice of Uncertain Programming

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Publisher : Physica
ISBN 13 : 3790817813
Total Pages : 384 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Theory and Practice of Uncertain Programming by : Baoding Liu

Download or read book Theory and Practice of Uncertain Programming written by Baoding Liu and published by Physica. This book was released on 2013-04-17 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-life decisions are usually made in the state of uncertainty (randomness, fuzziness, roughness, etc.). How do we model optimization problems in uncertain environments? How do we solve these models? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory. It includes numerous modeling ideas, hybrid intelligent algorithms, and various applications in transportation problem, inventory system, facility location & allocation, capital budgeting, topological optimization, vehicle routing problem, redundancy optimization, and scheduling. Researchers, practitioners and students in operations research, management science, information science, system science, and engineering will find this work a stimulating and useful reference.

Uncertainty Theory

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Publisher : Springer
ISBN 13 : 3642139590
Total Pages : 350 pages
Book Rating : 4.98/5 ( download)

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Book Synopsis Uncertainty Theory by : Baoding Liu

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer. This book was released on 2010-07-16 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Nonlinear Interval Optimization for Uncertain Problems

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Publisher : Springer Nature
ISBN 13 : 9811585466
Total Pages : 291 pages
Book Rating : 4.63/5 ( download)

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Book Synopsis Nonlinear Interval Optimization for Uncertain Problems by : Chao Jiang

Download or read book Nonlinear Interval Optimization for Uncertain Problems written by Chao Jiang and published by Springer Nature. This book was released on 2020-12-08 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.

Introduction to Stochastic Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 0387226184
Total Pages : 427 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Introduction to Stochastic Programming by : John R. Birge

Download or read book Introduction to Stochastic Programming written by John R. Birge and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.

Uncertain Data Envelopment Analysis

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Publisher : Springer
ISBN 13 : 366243802X
Total Pages : 157 pages
Book Rating : 4.22/5 ( download)

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Book Synopsis Uncertain Data Envelopment Analysis by : Meilin Wen

Download or read book Uncertain Data Envelopment Analysis written by Meilin Wen and published by Springer. This book was released on 2014-07-24 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4 and 5 provide two uncertain DEA methods to evaluate the DMUs with limited or insufficient statistical data, named fuzzy DEA and uncertain DEA. In order to evaluate the DMUs in which uncertainty and randomness appear simultaneously, the hybrid DEA based on chance theory is presented in Chapter 6.