Building and Solving Mathematical Programming Models in Engineering and Science (Hardcover)

Enrique Castillo

ISBN 10: 0471150436 / ISBN 13: 9780471150435

Published by John Wiley & Sons Inc, New York, 2001

About this Item

Hardcover. 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. Modeling is one of the most appealing areas in engineering and applied sciences. Engineers need to build models to solve real life problems. The aim of a model consists of reproducing the reality as faithfully as possible, trying to understand how the real world behaves, and obtaining the expected responses to given actions or inputs. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780471150435

Bibliographic Details

Title: Building and Solving Mathematical ...

Publisher: John Wiley & Sons Inc, New York

Publication Date: 2001

Binding: Hardcover

Condition: new

Edition: 1st Edition

About this title

Synopsis:

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.

About the Author:

ENRIQUE CASTILLO, PhD, is Full Professor of Applied Mathematics at the University of Cantabria in Santander, Spain.

ANTONIO J. CONEJO, PhD, is Full Professor of Electrical Engineering at the Universidad de Castilla La Mancha, Ciudad Real, Spain.

PABLO PEDREGAL, PhD, is Full Professor of Applied Mathematics at the University of Cantabria.

RICARDO GARCIA is a mathematician in the fields of optimization and operation research.

NATALIA ALGUACIL, PhD, researches optimization by decomposition techniques.