The Science of Decision Making: A Problem-Based Approach Using Excel / Edition 1

by Eric V. Denardo

Overview

The Science of Decision Making: A Problem-Based Introduction Using Excel, is a comprehensive, coherent, problems-based approach to learning the science of decision-making. It includes models of operations research for engineering, management, ecomomics and the sciences.

Intended for undergraduate and master's level students in engineering, management, economics, and the sciences taking courses in Operations Research, Introduction to Deterministic and Stochastic Methods, Management Science, Linear Programming, and Probabilistic Models.

Product Details

ISBN-13:	9780471318279
Publisher:	Wiley
Publication date:	08/28/2001
Pages:	720
Product dimensions:	8.31(w) x 10.31(h) x 1.26(d)

About the Author

Educated at Princeton and Northwestern Universities, Eric V. Denardo worked for AT&T and The Rand Corporation before joining the faculty of Yale University. His work is noted for its breadth, innovation, and elegance.

Table of Contents

Preface.

PART A: INTRODUCTION.

The Science of Decision Making.

Getting Started with Spreadsheets.

PART B: USING LINEAR PROGRAMS.

Analyzing Solutions of Linear Programs.

A Survey of Linear Programs.

Networks.

Integer Programs.

PART C: PROBABILITY FOR DECISION MAKING.

Introduction to Probability Models.

Discrete Random Variables.

Decision Trees and Generalizations.

Utility Theory and Decision Analysis.

Continuous Random Variables.

PART D: STOCHASTIC SYSTEMS.

Inventory.

Markov Chains.

Queueing.

Simulation.

PART E: GAME THEORY.

Game Theory.

PART F: SOLVING LINEAR PROGRAMS.

Solving Linear Equations.

The Simplex Method.

Duality.

Appendix: Note on Excel.

Index.

Editorial Reviews

This text/CD-ROM package introduces the science of decision making using a combination of problem-based learning, spreadsheet computation, and decision science. It emphasizes the links between operations research and economic reasoning, with inclusion of probability, but excludes nearly all of the algorithms that are a part of operations research, leaving them for more advanced courses. Examples are taken from engineering, economics, finance, operations management, business, and medical decision making. The text is useful for one-semester courses introducing deterministic models of decision making and stochastic methods. The CD-ROM contains Premium Solver for Education, TreePlan, and RiskSim, functions, and data sets. The author is on the faculty at Yale University. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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