Operations Research Models and Methods / Edition 1

by Paul A. Jensen, Jonathan F. Bard

Overview

In a rapidly developing field like Operations Research, its easy to get overwhelmed by the variety of topics and analytic techniques. Paul Jensen and Jonathan Bard help you master the expensive field by focusing on the fundamental models and methodologies underlying the practice of Operations Research.

Bridging the gap between theory and practice, the author presents the quantitative tools and models most important to understanding modern operations research. You'll come to appreciate the power of OR techniques in solving real-world problems and applications in your own field. You'll learn how to translate complex situations into mathematical models, solve models and turn models into solutions. This text is designed to bridge the gap between theory and practice by presenting the quantitative tools and models most suited for modern operations research. The principal goal is to give analysts, engineers, and decision makers a larger appreciation of their roles by defining a common terminology and by explaining the interfaces between the underlying methodologies.

Features

• Divides each subject into methods and models, giving you greater flexibility in how you approach the material.
• Concise and focused presentation highlights central ideas.
• Many examples throughout the text will help you better understand mathematical material.

Product Details

ISBN-13:	9780471380047
Publisher:	Wiley
Publication date:	10/08/2002
Pages:	704
Product dimensions:	8.26(w) x 10.78(h) x 1.49(d)

About the Author

Paul A. Jensen and Jonathan F. Bard are the authors of Operations Research Models and Methods, published by Wiley.

Table of Contents

Problem Solving With Operations Research.

Linear Programming Models.

Linear Programming Methods.

Sensitivity Analysis, Duality, and Interior Point Methods.

Network Flow Programming Models.

Network Flow Programming Methods.

Integer Programming Models.

Integer Programming Methods.

Nonlinear Programming Models.

Nonlinear Programming Methods.

Models for Stochastic Processes.

Discrete-Time Markov Chains.

Mathematics of Discrete-Time Markov Chains.

Continuous-Time Markov Chains.

Mathematics of Continuous-Time Markov Chains.

Queuing Models.

Queuing Networks and Decision Models.

Simulation.

Index.