The Science Of Decision Making: A Problem-Based Approach Using Excel

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.

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.

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.