Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson

Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson Tài liệu An introduction to management science quantitative approaches to decision making 2nd anderson

David R Anderson l Dennis J Sweeney Thomas A Williams l Mik Wisniewski AN INTRODUCTION TO MANAGEMENT SCIENCE QUANTITATIVE APPROACHES TO DECISION MAKING second edition Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it This is an electronic version of the print textbook Due to electronic rights restrictions, some third party content may be suppressed Editorial review has deemed that any suppressed content does not materially affect the overall learning experience The publisher reserves the right to remove content from this title at any time if subsequent rights restrictions require it For valuable information on pricing, previous editions, changes to current editions, and alternate formats, please visit www.cengage.com/highered to search by ISBN#, author, title, or keyword for materials in your areas of interest Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it An Introduction to Management Science: Quantitative Approaches to Decision Making, 2nd Edition Anderson, Sweeney, Williams and Wisniewski Publisher: Andrew Ashwin Development Editor: Felix Rowe Senior Production Editor: Alison Burt Editorial Assistant: Jenny Grene Senior Manufacturing Buyer: Eyvett Davis Typesetter: Integra Software Services PVT LTD Cover design: Adam Renvoize Text design: Design Deluxe Ó 2014, Cengage Learning EMEA WCN: 02-300 ALL RIGHTS RESERVED No part of this work covered by the copyright herein may be reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, or applicable copyright law of another jurisdiction, without the prior written permission of the publisher While the publisher has taken all reasonable care in the preparation of this book, the publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions from the book or the consequences thereof Products and services that are referred to in this book may be either trademarks and/or registered trademarks of their respective owners The publishers and author/s make no claim to these trademarks The publisher does not endorse, and accepts no responsibility or liability for, incorrect or defamatory content contained in hyperlinked material All the URLs in this book are correct at the time of going to press; however the Publisher accepts no responsibility for the content and continued availability of third party websites For product information and technology assistance, contact emea.info@cengage.com For permission to use material from this text or product, and for permission queries, email emea.permissions@cengage.com British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-4080-8840-1 Cengage Learning EMEA Cheriton House, North Way, Andover, Hampshire, SP10 5BE United Kingdom Cengage Learning products are represented in Canada by Nelson Education Ltd For your lifelong learning solutions, visit www.cengage.co.uk Purchase your next print book, e-book or e-chapter at www.cengagebrain.com Printed by Croatia By Zrinsky d.d 10 – 16 15 14 Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Brief contents About the Authors xi Preface xiii Acknowledgements xv Introduction An Introduction to Linear Programming 33 Linear Programming: Sensitivity Analysis and Interpretation of Solution 85 Linear Programming Applications 137 Linear Programming: The Simplex Method 211 Simplex-Based Sensitivity Analysis and Duality 254 Transportation, Assignment and Transshipment Problems 279 Network Models 344 Project Scheduling: PERT/CPM 370 10 Inventory Models 405 11 Queuing Models 451 12 Simulation 489 13 Decision Analysis 539 14 Multicriteria Decisions 593 Conclusion: Management Science in Practice 635 Appendices 639 Appendix A Areas for the Standard Normal Distribution 641 Appendix B Values of e l 642 Appendix C Bibliography and References 643 Appendix D Self-Test Solutions 645 Glossary 677 Index 683 ONLINE CONTENTS 15 Integer Linear Programming 16 Forecasting 17 Dynamic Programming 18 Markov Processes iii Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it Contents About the Authors xi Preface xiii Acknowledgements xv Introduction 1.1 Introduction to Management Science Does it Work? 1.2 Where Did MS Come From? 1.3 Management Science Applications Assignment Data Mining Financial Decision Making Forecasting Logistics Marketing Networks Optimization Project Planning and Management Queuing Simulation Transportation 1.4 The MS Approach Problem Recognition Problem Structuring and Definition Modelling and Analysis 10 Solutions and Recommendations 11 Implementation 11 1.5 Models 12 1.6 Models of Cost, Revenue and Profit 15 Cost and Volume Models 15 Revenue and Volume Models 16 Profit and Volume Models 17 Breakeven Analysis 17 1.7 The Modelling Process 18 1.8 Management Science Models and Techniques 20 Linear Programming 20 Transportation and Assignment 20 Network Models 20 Project Management 20 Inventory Models 21 Queuing Models 21 Simulation 21 Decision Analysis 21 Multicriteria analysis 21 Integer Linear Programming 21 Forecasting 21 Dynamic Programming 22 Markov Process Models 22 Summary 22 Worked Example 22 Problems 24 Case Problem Uhuru Craft Cooperative, Tanzania 27 Appendix 1.1 Using Excel for Breakeven Analysis 27 Appendix 1.2 The Management Scientist Software 30 An Introduction to Linear Programming 33 2.1 A Maximization Problem 35 Problem Formulation 36 Mathematical Statement of the GulfGolf Problem 39 2.2 Graphical Solution Procedure 40 A Note on Graphing Lines 48 Summary of the Graphical Solution Procedure for Maximization Problems 50 Slack Variables 51 2.3 Extreme Points and the Optimal Solution 53 2.4 Computer Solution of the GulfGolf Problem 54 Interpretation of Computer Output 55 2.5 A Minimization Problem 57 Summary of the Graphical Solution Procedure for Minimization Problems 58 Surplus Variables 59 Computer Solution of the M&D Chemicals Problem 61 2.6 Special Cases 62 Alternative Optimal Solutions 62 Infeasibility 63 Unbounded Problems 64 2.7 General Linear Programming Notation 66 Summary 67 Worked Example 68 Problems 71 v Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it vi CONTENTS Case Problem Workload Balancing 76 Case Problem Production Strategy 77 Case Problem Blending 78 Appendix 2.1 Solving Linear Programmes With Excel 79 Appendix 2.2 Solving Linear Programmes With the Management Scientist 82 Linear Programming: Sensitivity Analysis and Interpretation of Solution 85 3.1 Introduction to Sensitivity Analysis 86 3.2 Graphical Sensitivity Analysis 88 Objective Function Coefficients 88 Right-Hand Sides 93 3.3 Sensitivity Analysis: Computer Solution 97 Interpretation of Computer Output 97 Simultaneous Changes 99 Interpretation of Computer Output – A Second Example 101 Cautionary Note on the Interpretation of Dual Prices 104 3.4 More than Two Decision Variables 105 The Modified GulfGolf Problem 106 The Kenya Cattle Company Problem 109 Formulation of the KCC Problem 111 Computer Solution and Interpretation for the KCC Problem 112 3.5 The Taiwan Electronic Communications (TEC) Problem 115 Problem Formulation 116 Computer Solution and Interpretation 117 Summary 121 Worked Example Problems 123 Case Problem Case Problem Case Problem 121 Product Mix 134 Investment Strategy 135 Truck Leasing Strategy 136 4.5 Financial Applications 168 Portfolio Selection 170 Financial Planning 174 Revenue Management 178 4.6 Data Envelopment Analysis 182 Summary 190 Problems 191 Case Problem Planning an Advertising Campaign 200 Case Problem Phoenix Computer 202 Case Problem Textile Mill Scheduling 202 Case Problem Workforce Scheduling 204 Case Problem Cinergy Coal Allocation 205 Appendix 4.1 Excel Solution of Hewlitt Corporation Financial Planning Problem 207 Linear Programming: The Simplex Method 211 5.1 An Algebraic Overview of the Simplex Method 212 Algebraic Properties of the Simplex Method 213 Determining a Basic Solution 213 Basic Feasible Solution 214 5.2 Tableau Form 216 5.3 Setting Up the Initial Simplex Tableau 217 5.4 Improving the Solution 218 5.5 Calculating the Next Tableau 222 Interpreting the Results of an Iteration 224 Moving Toward a Better Solution 225 Interpreting the Optimal Solution 228 Summary of the Simplex Method 228 Linear Programming Applications 137 5.6 Tableau Form: The General Case 230 Greater-Than-or-Equal-to Constraints (‡) 230 Equality Constraints 234 Eliminating Negative Right-Hand Side Values 235 Summary of the Steps to Create Tableau Form 236 4.1 The Process of Problem Formulation 138 5.7 Solving a Minimization Problem 237 4.2 Production Management Applications 140 Make-or-Buy Decisions 140 Production Scheduling 143 Workforce Assignment 150 4.3 Blending, Diet and Feed-Mix Problems 156 5.8 Special Cases 239 Infeasibility 239 Unbounded Problems 240 Alternative Optimal Solutions 242 Degeneracy 243 4.4 Marketing and Media Applications 163 Media Selection 163 Marketing Research 166 Summary 244 Worked Example 245 Problems 248 Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it CONTENTS Simplex-Based Sensitivity Analysis and Duality 254 Case Problem Distribution System Design 336 Appendix 7.1 Excel Solution of Transportation, Assignment and Transshipment Problems 338 6.1 Sensitivity Analysis with the Simplex Tableau 255 Objective Function Coefficients 255 Right-Hand Side Values 258 Simultaneous Changes 265 Network Models 6.2 Duality 266 Interpretation of the Dual Variables 268 Using the Dual to Identify the Primal Solution 270 Finding the Dual of Any Primal Problem 270 344 8.1 Shortest-Route Problem 345 A Shortest-Route Algorithm 346 8.2 Minimal Spanning Tree Problem 354 A Minimal Spanning Tree Algorithm 355 8.3 Maximal Flow Problem 357 Summary 272 Worked Example 273 Problems 274 Summary 362 Worked Example 362 Problems 363 Case Problem Ambulance Routing 368 Transportation, Assignment and Transshipment Problems 279 Project Scheduling: PERT/CPM 370 7.1 Transportation Problem: A Network Model and a Linear Programming Formulation 280 Problem Variations 283 A General Linear Programming Model of the Transportation Problem 285 9.1 Project Scheduling With Known Activity Times 372 The Concept of a Critical Path 373 Determining the Critical Path 374 Contributions of PERT/CPM 378 Summary of the PERT/CPM Critical Path Procedure 379 Gantt Charts 380 7.2 Transportation Simplex Method: A SpecialPurpose Solution Procedure 286 Phase I: Finding an Initial Feasible Solution 288 Phase II: Iterating to the Optimal Solution 291 Summary of the Transportation Simplex Method 300 Problem Variations 302 7.3 Assignment Problem: The Network Model and a Linear Programming Formulation 303 Problem Variations 305 A General Linear Programming Model of the Assignment Problem 306 Multiple Assignments 307 7.4 Assignment Problem: A Special-Purpose Solution Procedure 307 Finding the Minimum Number of Lines 311 Problem Variations 311 7.5 Transshipment Problem: The Network Model and a Linear Programming Formulation 314 Problem Variations 319 A General Linear Programming Model of the Transshipment Problem 320 7.6 A Production and Inventory Application 320 Summary 324 Worked Example 325 Problems 327 vii 9.2 Project Scheduling With Uncertain Activity Times 381 The Daugherty Porta-Vac Project 382 Uncertain Activity Times 382 The Critical Path 385 Variability in Project Completion Time 386 9.3 Considering Time–Cost Trade-Offs 388 Crashing Activity Times 389 Summary 392 Worked Example 392 Problems 394 Case Problem R.C Coleman 401 Appendix 9.1 Activity on Arrow Networks 402 10 Inventory Models 405 10.1 Principles of Inventory Management 406 The Role of Inventory 406 Inventory Costs 407 10.2 Economic Order Quantity (EOQ) Model 408 The How-Much-to-Order Decision 411 The When-to-Order Decision 413 Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it viii CONTENTS Sensitivity Analysis for the EOQ Model 414 Excel Solution of the EOQ Model 415 Summary of the EOQ Model Assumptions 415 10.3 Economic Production Lot Size Model 416 Total Cost Model 418 Economic Production Lot Size 420 10.4 Inventory Model with Planned Shortages 421 10.5 Quantity Discounts for the EOQ Model 425 10.6 Single-Period Inventory Model with Probabilistic Demand 427 Juliano Shoe Company 428 Arabian Car Rental 431 10.7 Order-Quantity, Reorder Point Model with Probabilistic Demand 433 The How-Much-to-Order Decision 434 The When-to-Order Decision 435 10.8 Periodic Review Model with Probabilistic Demand 437 More Complex Periodic Review Models 440 Summary 441 Worked Example 442 Problems 443 Case Problem Wagner Fabricating Company 447 Case Problem River City Fire Department 448 Appendix 10.1 Development of the Optimal Order Quantity (Q) Formula for the EOQ Model 449 Appendix 10.2 Development of the Optimal Lot Size (Q*) Formula for the Production Lot Size Model 450 11 Queuing Models 451 11.1 Structure of a Queuing System 452 Single-Channel Queue 454 Distribution of Arrivals 454 Distribution of Service Times 455 Steady-State Operation 456 11.4 Some General Relationships for Queuing Models 466 11.5 Economic Analysis of Queues 468 11.6 Other Queuing Models 470 11.7 Single-Channel Queuing Model with Poisson Arrivals and Arbitrary Service Times 471 Operating Characteristics for the M/G/1 Model 471 Constant Service Times 472 11.8 Multiple-Channel Model with Poisson Arrivals, Arbitrary Service Times and No Queue 473 Operating Characteristics for the M/G/k Model with Blocked Customers Cleared 473 11.9 Queuing Models with Finite Calling Populations 476 Operating Characteristics for the M/M/1 Model with a Finite Calling Population 476 Summary 479 Worked Example 479 Problems 481 Case Problem Regional Airlines 486 Case Problem Office Equipment, Inc 487 12 Simulation 489 12.1 Risk Analysis 492 PortaCom Project 492 What-If Analysis 492 Simulation 493 Simulation of the PortaCom Problem 501 12.2 Inventory Simulation 504 Simulation of the Butler Inventory Problem 507 11.2 Single-Channel Queuing Model with Poisson Arrivals and Exponential Service Times 456 Operating Characteristics 457 Operating Characteristics for the Dome Problem 458 Managers’ Use of Queuing Models 458 Improving the Queuing Operation 459 Excel Solution of the Queuing Model 461 12.3 Queuing Simulation 509 Hong Kong Savings Bank ATM Queuing System 510 Customer Arrival Times 510 Customer Service Times 511 Simulation Model 511 Simulation of the ATM Problem 515 Simulation with Two ATMs 516 Simulation Results with Two ATMs 518 11.3 Multiple-Channel Queuing Model with Poisson Arrivals and Exponential Service Times 462 Operating Characteristics 462 Operating Characteristics for the Dome Problem 464 12.4 Other Simulation Issues 520 Computer Implementation 520 Verification and Validation 521 Advantages and Disadvantages of Using Simulation 522 Copyright 2014 Cengage Learning All Rights Reserved May not be copied, scanned, or duplicated, in whole or in part Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s) Editorial review has deemed that any suppressed content does not materially affect the overall learning experience Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it ... right to remove additional content at any time if subsequent rights restrictions require it An Introduction to Management Science: Quantitative Approaches to Decision Making, 2nd Edition Anderson, ...David R Anderson l Dennis J Sweeney Thomas A Williams l Mik Wisniewski AN INTRODUCTION TO MANAGEMENT SCIENCE QUANTITATIVE APPROACHES TO DECISION MAKING second edition Australia • Brazil • Japan •... provides an overall introduction to the text; the origins and developments in management science are outlined; there are detailed examples of areas in business and management where management science