Applied Mathematical Programming

Applied Mathematical Programming PDF

Author: Stephen P. Bradley

Publisher: Addison Wesley Publishing Company

Published: 1977

Total Pages: 748

ISBN-13:

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Mathematical programming: an overview; solving linear programs; sensitivity analysis; duality in linear programming; mathematical programming in practice; integration of strategic and tactical planning in the aluminum industry; planning the mission and composition of the U.S. merchant Marine fleet; network models; integer programming; design of a naval tender job shop; dynamic programming; large-scale systems; nonlinear programming; a system for bank portfolio planning; vectors and matrices; linear programming in matrix form; a labeling algorithm for the maximun-flow network problem.

Mathematical Programming for Industrial Engineers

Mathematical Programming for Industrial Engineers PDF

Author: Mordecai Avriel

Publisher: CRC Press

Published: 1996-05-16

Total Pages: 662

ISBN-13: 9780824796204

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Setting out to bridge the gap between the theory of mathematical programming and the varied, real-world practices of industrial engineers, this work introduces developments in linear, integer, multiobjective, stochastic, network and dynamic programing. It details many relevant industrial-engineering applications.;College or university bookstores may order five or more copies at a special student price, available upon request from Marcel Dekker, Inc.

Building and Solving Mathematical Programming Models in Engineering and Science

Building and Solving Mathematical Programming Models in Engineering and Science PDF

Author: Enrique Castillo

Publisher: John Wiley & Sons

Published: 2011-10-24

Total Pages: 568

ISBN-13: 0471461652

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Fundamental concepts of mathematical modeling Modeling is one of the most effective, commonly used tools in engineering and the applied sciences. In this book, the authors deal with mathematical programming models both linear and nonlinear and across a wide range of practical applications. Whereas other books concentrate on standard methods of analysis, the authors focus on the power of modeling methods for solving practical problems-clearly showing the connection between physical and mathematical realities-while also describing and exploring the main concepts and tools at work. This highly computational coverage includes: * Discussion and implementation of the GAMS programming system * Unique coverage of compatibility * Illustrative examples that showcase the connection between model and reality * Practical problems covering a wide range of scientific disciplines, as well as hundreds of examples and end-of-chapter exercises * Real-world applications to probability and statistics, electrical engineering, transportation systems, and more Building and Solving Mathematical Programming Models in Engineering and Science is practically suited for use as a professional reference for mathematicians, engineers, and applied or industrial scientists, while also tutorial and illustrative enough for advanced students in mathematics or engineering.

Decomposition Techniques in Mathematical Programming

Decomposition Techniques in Mathematical Programming PDF

Author: Antonio J. Conejo

Publisher: Springer Science & Business Media

Published: 2006-04-28

Total Pages: 542

ISBN-13: 3540276866

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Optimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning procedure. For the sake of cl- ity, theoretical concepts and computational algorithms are assembled based on these examples. The results are simplicity, clarity, and easy-learning. We feel that this book is needed by the engineering community that has to tackle complex optimization problems, particularly by practitioners and researchersinEngineering,OperationsResearch,andAppliedEconomics.The descriptions of most decomposition techniques are available only in complex and specialized mathematical journals, di?cult to understand by engineers. A book describing a wide range of decomposition techniques, emphasizing problem-solving, and appropriately blending theory and application, was not previously available.

Applied Mathematical Programming for Business and Economics

Applied Mathematical Programming for Business and Economics PDF

Author: Man-Keun Kim

Publisher: World Scientific Publishing Company

Published: 2025-01-31

Total Pages: 0

ISBN-13: 9789811254116

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This introductory/intermediate level textbook focuses on mathematical programming and its applications. It introduces basic linear programming -- the easiest form of mathematical programming with emphasis on economic interpretation of the model solution. Well-known applications of linear programming to problems in business and agriculture are presented.The text then extends into more advanced forms of mathematical programming including quadratic and integer programming. These models include the introduction of risk and uncertainty into decision-making and a class of models known as price endogenous models in which market equilibrium analyses can be modelled. Integer programming includes conditional decision-making model, machinery selection, and a class of models known as supply chain models.Supplements are provided to assist solution of the models using either GAMS or Excel, the two most widely used software packages for solution of mathematical programming models.

Mathematical Programming with Data Perturbations

Mathematical Programming with Data Perturbations PDF

Author: Anthony V. Fiacco

Publisher: CRC Press

Published: 1997-09-19

Total Pages: 460

ISBN-13: 9780824700591

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Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.

Mathematical Programming

Mathematical Programming PDF

Author: Michel Minoux

Publisher: John Wiley & Sons

Published: 1986

Total Pages: 526

ISBN-13:

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This comprehensive work covers the whole field of mathematical programming, including linear programming, unconstrained and constrained nonlinear programming, nondifferentiable (or nonsmooth) optimization, integer programming, large scale systems optimization, dynamic programming, and optimization in infinite dimensions. Special emphasis is placed on unifying concepts such as point-to-set maps, saddle points and perturbations functions, duality theory and its extensions.

Mathematical Programming with Data Perturbations

Mathematical Programming with Data Perturbations PDF

Author: Anthony V. Fiacco

Publisher: CRC Press

Published: 2020-09-24

Total Pages: 460

ISBN-13: 1000153665

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Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.