Solutions Manual - To Decision Making Thirteenth Edition (Revised)...

Solutions Manual For An Introduction To Management Science Quantitative Approaches To Decision Making Thirteenth Edition (Revised) David R. Anderson Dennis J. Sweeney Thomas A. Williams Jeffrey D. Camm

• Kipp Martin

Part 1: Solutions Manual: Page 1-420 Part 2: Case Solutions: Page 421-514 1 / 4

Contents Chapter 1.Introduction 2.An Introduction to Linear Programming

3.Linear Programming: Sensitivity Analysis and Interpretation of Solution

4.Linear Programming Applications in Marketing, Finance and Operations Management 5.Advanced Linear Programming Applications 6.Distribution and Network Models 7.Integer Linear Programming 8.Nonlinear Optimization Models

9.Project Scheduling: PERT/CPM

10.Inventory Models 11.Waiting Line Models 12.Simulation 13.Decision Analysis 14.Multicriteria Decision Problems 15.Forecasting 16.Markov Processes

17.Linear Programming: The Simplex Method

18.Simplex-Based Sensitivity Analysis and Duality 19.Solution Procedures for Transportation and Assignment Problems 20.Minimal Spanning Tree 21.Dynamic Programming

Appendix A: Building Spreadsheet Models

Part 1: Solutions Manual 2 / 4

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© 2010 Cengage Learning. All Rights Reserved.May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.Chapter 1 Introduction

Learning Objectives

• Develop a general understanding of the management science/operations research approach to decision

making.

• Realize that quantitative applications begin with a problem situation.

• Obtain a brief introduction to quantitative techniques and their frequency of use in practice.

• Understand that managerial problem situations have both quantitative and qualitative considerations

that are important in the decision making process.

• Learn about models in terms of what they are and why they are useful (the emphasis is on mathematical

models).

• Identify the step-by-step procedure that is used in most quantitative approaches to decision making.

• Learn about basic models of cost, revenue, and profit and be able to compute the breakeven point.

• Obtain an introduction to the use of computer software packages such as Microsoft Excel in applying

quantitative methods to decision making.

9. Understand the following terms:

model infeasible solution objective function management science constraint operations research deterministic model fixed cost stochastic model variable cost feasible solution breakeven point

Solutions: 3 / 4

Chapter 1

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© 2010 Cengage Learning. All Rights Reserved.May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

• Management science and operations research, terms used almost interchangeably, are broad

disciplines that employ scientific methodology in managerial decision making or problem solving. Drawing upon a variety of disciplines (behavioral, mathematical, etc.), management science and operations research combine quantitative and qualitative considerations in order to establish policies and decisions that are in the best interest of the organization.

• Define the problem

Identify the alternatives

Determine the criteria

Evaluate the alternatives

Choose an alternative

For further discussion see section 1.3

• See section 1.2.

• A quantitative approach should be considered because the problem is large, complex, important,

new and repetitive.

• Models usually have time, cost, and risk advantages over experimenting with actual situations.

• Model (a) may be quicker to formulate, easier to solve, and/or more easily understood.

• Let d = distance

m = miles per gallon c = cost per gallon,

Total Cost =2d c m







We must be willing to treat m and c as known and not subject to variation.

• Maximize 10x + 5y

s.t.5x + 2y  40 x  0, y  0

b. Controllable inputs: x and y

Uncontrollable inputs: profit (10,5), labor hours (5,2) and labor-hour availability (40)

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