Introduction to managerment science a modeling and case studies approach with spreadsheets 6e hillier

page i www.freebookslides.com page ii The McGraw-Hill/Irwin Series in Operations and Decision Sciences SUPPLY CHAIN MANAGEMENT Benton Purchasing and Supply Chain Management Second Edition Burt, Petcavage, and Pinkerton Supply Management Eighth Edition Bowersox, Closs, Cooper, and Bowersox Supply Chain Logistics Management Fourth Edition Johnson and Flynn Purchasing and Supply Management Fifteenth Edition Simchi-Levi, Kaminsky, and Simchi-Levi Designing and Managing the Supply Chain: Concepts, Strategies, Case Studies Third Edition PROJECT MANAGEMENT Brown and Hyer Managing Projects: A Team-Based Approach First Edition Larson and Gray Project Management: The Managerial Process Seventh Edition SERVICE OPERATIONS MANAGEMENT Bordoloi, Fitzsimmons, and Fitzsimmons Service Management: Operations, Strategy, Information Technology Ninth Edition MANAGEMENT SCIENCE Hillier and Hillier Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets Sixth Edition Stevenson and Ozgur Introduction to Management Science with Spreadsheets First Edition MANUFACTURING CONTROL SYSTEMS www.freebookslides.com Jacobs, Berry, Whybark, and Vollmann Manufacturing Planning & Control for Supply Chain Management Sixth Edition BUSINESS RESEARCH METHODS Cooper and Schindler Business Research Methods Twelfth Edition BUSINESS FORECASTING Keating and Wilson Business Forecasting Seventh Edition LINEAR STATISTICS AND REGRESSION Kutner, Nachtsheim, and Neter Applied Linear Regression Models Fourth Edition BUSINESS SYSTEMS DYNAMICS Sterman Business Dynamics: Systems Thinking and Modeling for a Complex World First Edition OPERATIONS MANAGEMENT Cachon and Terwiesch Operations Management First Edition Cachon and Terwiesch Matching Supply with Demand: An Introduction to Operations Management Third Edition Finch Interactive Models for Operations and Supply Chain Management First Edition Jacobs and Chase Operations and Supply Chain Management Fifteenth Edition Jacobs and Chase Operations and Supply Chain Management: The Core Fourth Edition Jacobs and Whybark Why ERP? 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Edition Jaggia and Kelly Business Statistics: Communicating with Numbers Third Edition Jaggia and Kelly Essentials of Business Statistics: Communicating with Numbers First Edition McGuckian Connect Master: Business Statistics Introduction to Management Science www.freebookslides.com page iii Introduction to Management Science A Modeling and Case Studies Approach with Spreadsheets Sixth Edition Frederick S Hillier Stanford University Mark S Hillier University of Washington Cases developed by Karl Schmedders University of Zurich Molly Stephens Quinn, Emanuel, Urquhart & Sullivan, LLP www.freebookslides.com page iv INTRODUCTION TO MANAGEMENT SCIENCE: A MODELING AND CASE STUDIES APPROACH WITH SPREADSHEETS, SIXTH EDITION Published by McGraw-Hill Education, Penn Plaza, New York, NY 10121 Copyright © 2019 by McGraw-Hill Education All rights reserved Printed in the United States of America Previous editions © 2014, 2011, and 2008 No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of McGraw-Hill Education, including, but not limited to, in any network or other electronic storage or transmission, or broadcast for distance learning Some ancillaries, including electronic and print components, may not be available to customers outside the United States This book is printed on acid-free paper QVS 21 20 19 18 ISBN   978-1-259-91892-6 MHID 1-259-91892-0 Portfolio Manager: Noelle Bathurst Lead Product Developer: Michele Janicek Product Developer: Tobi Phillips Executive Marketing Manager: Harper Christopher Content Project Managers: Erika Jordan and Jamie Koch Buyer: Susan K Culbertson Design: Jessica Cuevas Content Licensing Specialist: Brianna Kirschbaum Cover Image: ©polygraphus/Getty Images Compositor: SPi Global All credits appearing on page or at the end of the book are considered to be an extension of the copyright page Library of Congress Cataloging-in-Publication Data Names: Hillier, Frederick S., author | Hillier, Mark S., author www.freebookslides.com Title: Introduction to management science : a modeling and case studies approach with spreadsheets / Frederick S Hillier, Stanford University, Mark S Hillier, University of Washington ; cases developed by Karl Schmedders, University of Zurich, Molly Stephens, Quinn, Emanuel, Urquhart & Sullivan, LLP Description: Sixth edition | New York, NY : McGraw-Hill Education, [2019] Identifiers: LCCN 2017048567| ISBN 9781259918926 (acid-free paper) | ISBN 1259918920 (acidfree paper) Subjects: LCSH: Management science | Operations research Classification: LCC T56 H55 2019 | DDC 658.4/032 dc22 LC record available at https://lccn.loc.gov/2017048567 The Internet addresses listed in the text were accurate at the time of publication The inclusion of a website does not indicate an endorsement by the authors or McGraw-Hill Education, and McGrawHill Education does not guarantee the accuracy of the information presented at these sites mheducation.com/highered www.freebookslides.com page v To the memory of Christine Phillips Hillier a beloved wife and daughter-in-law Gerald J Lieberman an admired mentor and one of the true giants of our field www.freebookslides.com page vi About the Authors Frederick S Hillier is professor emeritus of operations research at Stanford University Dr Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J Lieberman, which has been translated into well over a dozen languages and is currently in its 10th edition The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field), and Dr Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University The winner of many awards in high school and college for writing, mathematics, debate, and music, he ranked first in his undergraduate engineering class and was awarded three national fellowships (National Science Foundation, Tau Beta Pi, and Danforth) for graduate study After receiving his PhD degree, he joined the faculty of Stanford University, where he earned tenure at the age of 28 and the rank of full professor at 32 Dr Hillier’s research has extended into a variety of areas, including integer programming, queueing theory and its application, statistical quality control, and production and operations management He also has won a major prize for research in capital budgeting Twice elected a national officer of professional societies, he has served in many important professional and editorial capacities For example, he served The Institute of Management Sciences as vice president for meetings, chairman of the publications committee, associate editor of Management Science, and co-general chairman of an international conference in Japan He also is a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS) He served for 20 years (until 2013) as the founding series editor for a prominent book series, the International Series in Operations Research and Management Science, for Springer Science + Business Media He has had visiting appointments at Cornell University, the Graduate School of Industrial Administration of Carnegie-Mellon University, the Technical University of Denmark, the University of Canterbury (New Zealand), and the Judge Institute of Management Studies at the University of Cambridge (England) Mark S Hillier, son of Fred Hillier, is associate professor of quantitative methods at the Michael G Foster School of Business at the University of Washington Dr Hillier received his BS in engineering (plus a concentration in computer science) from Swarthmore College He then received his MS with distinction in operations research 10 www.freebookslides.com assumptions, 475 Prescriptive analytics, 3, 12–13 Pri-Zan, H., 296 Prior probabilities, 337 Priority classes, 474 Priority procedure, 450 Priority queueing models, 474–479 general assumptions, 474 nonpreemptive priorities, 474 preemptive priorities, 474 Probabilities, queueing performance and, 457 Probability density function, 568 Probability distribution, 423 generating random observations, 509, 514–515 shifting distributions, 424–425 triangular distribution, 553 Probability tree diagram, 354 Process approach, 527 Product mix, 25 Product-mix case study, 25–27 algebraic approach to, 33–35 Analytic Solver, 43–47 background to, 25 data for, 27 graphical method, 35–39 linear programming model, 31–32 management science and, 26–27 management’s discussion, 25–26 as resource-allocation problem, 72–73 Solver and, 39–43 spreadsheet formulation of problem, 27–32 mathematical model in, 34–36 what-if analysis, 154–156 Production planning, 75 Production rates, 26, 28 Profit, 80 Project management, computer simulation and Solver, 591–595 parameter analysis report, 584–585 probability of meeting deadline, 552–553 sensitivity chart, 556–557 simulation results, 555–556 spreadsheet model, 553–555 Project selection, BIP for, 251–253 Project selection problem, 253 Proportional relationship, 281–284 997 www.freebookslides.com page 621 Proportionality assumption, 32, 270 Pure BIP model, 243–244 Puterman, M L., 344 Q Quadratic programming, 292, 297 Quadratic (Quadratic Solver), 318 Quantitative decision sciences, 12 Quantitative factors, 5–6 Queue, 447, 450 Queue capacity, 450 Queue discipline, 450 Queue size, 450 Queueing model arrivals, 448–449 elements of, 447–453 example of, 448 exponential distribution interarrival times, 449–450 random arrivals, 449 labels for, 452 the queue, 450–451 service, 451 service time distributions, 451–452 summary of assumptions, 452–453 Queueing models, 446 multiple-server models, 469–474 application of, 470–473 M/M/s model, 470 M/D/s model, 473 priority queueing models, 474–479 single-server models, 461–469 M/G/1 model, 466–469 M/M/1 model, 461–466 Queueing network, 448 Queueing systems, 446–447 basis system, 447 case study, 458–460 design insights, 480–484 economic analysis, number of servers, 485–488 examples of, 453–454 internal service systems, 484 measures of performance for, 455–457 998 www.freebookslides.com defining measures, 455–456 Little’s formula, 456 using probabilities, 457 transportation service systems, 484 Queueing theory, 446 Queues, 446 R Random arrivals, 449 Random number, 501 Random selection, 450 Random variable, 423 Range name, 7, 28, 139 Range of uncertainty, 180 Regression equation, 428 Relative reference, 30 Resource-allocation problems, 71–81; see also Capital budgeting characteristics of, 72–75 identifying feature of, 71 spreadsheet model formulation, 73–74 summary of formulation, 75, 80–81 Resource constraint, 71, 80, 88, 102 Results cells, 540 Revenue management (case study), 562–567 overbooking problem, 562–563 parameter analysis report, 585–597 simulation results, 566–567 spreadsheet model, 563–565 Risk analysis problem (case study), 557–562 decision variables, 559 results cells, 559 simulation results, 561–562 spreadsheet model, 559–561 statistic cell, 559 uncertain variable cells, 559 Risk-averse individual, 368 Risk-neutral individual, 368 Risk profile, 557–558 Risk seeker, 368 Robust optimization, 179–180 general procedures for, 181 independent parameters, 180–181 Robust solution, 180 Romeo-Hernandez, O., 76 Romo, F., 216 999 www.freebookslides.com S Saber metrics, 13 Sahoo, S., 245 Salesforce composite, 432 Samsung Electronics Corp., Ltd., 51 Schrijver, A., 259 Schuster, E W., 137 Scientific approach, 4–5 Scientific method, steps in systematic investigation, Seasonal effects, 404–406 Seasonal factor, 405 Seasonally adjusted time series, 406–407 Seif, M., 26 Sensitive parameter, 152, 162, 179–180 Sensitivity analysis, 153, 156, 346, 364 data table and, 346–350 in finding allowable range, 160–162 parameter analysis report, 158–160 sequence of decisions, 364–367 data table, 364–367 organizing spreadsheet, 364 simultaneous changes in constraints, 175–179 single changes in a constraint, 169–175 spreadsheet use in, 156–158 Sensitivity chart, 556–557 Sensitivity report, 186–188 key information from, 173–175, 178–179 Separable programming, 299–308 decreasing marginal returns, 299–303 example of, 304–307 smooth profit graphs, 303–304 Sequence of decisions, 357 Server, 447 Service, 451 Service cost, 485 Service time, 451 Service time distributions, 451–452 Set covering constraint, 255 Set covering problem, 255 Shadow price, 172 Shortest path problems, 212, 219–228 applications, 221–223 assumptions of, 221 example of, 219–221 general characteristics, 221 minimizing total costs (example), 223–224 1000 www.freebookslides.com minimizing total time (example), 224–228 model formulation, 219–221 Simplex LP (Linear solver), 318 Simplex method linear programming, 3, 210 network simplex method, 210, 212 Simulation clock, 516 Simulation model, 515 testing validity of, 521–522 Single-server queueing models, 461–469 M/M/1 model, 461–466 Single-server system, 451 Sink, 216 Site selection project, 253 SmartBook, 18 Smoothing constant, 414 Soft constraint, 179 Solis, F., 76 Solution, 34 Solver (Excel), 39, 587 Analytic Solver, 43–47 linear programming problems, 39–42 minimization problem, 50–51 personnel scheduling, 85 Source, 216 Spaghetti code, 126 Special Products Company break-even analysis, 6–11 Special-purpose algorithms, 212 Sports analytics, 13 Spreadsheet, mathematical model in, 33–35 Spreadsheet model, assignment problem, 100 break-even analysis, 6–8 break-even point, 10–11 capital budgeting, 78 cost-benefit-trade-off problems template, 87 debugging, 142–145 page 622 minimization problem, 48–50 mixed problems template, 94 nonlinear programming problem, 292–294 product-mix problem, 27–31 project management, 553–555 revenue management (case study), 563–565 1001 www.freebookslides.com transportation problem, 97–99 Spreadsheet software computer simulation, 527 decision trees, 343–344 management science, 1–2 Stable, 426 Stable time series, 425 Standard error, 545 State of the system, 516 States of nature, 336 Statistic cell, 540–541 Statistical forecasting methods, 397, 431 Statistics, 12 Steady-state condition, 455 Steenbeck, A., 259 Stenstrom, C., 93 Stochastic system, 500 Structural constraints, 34 Sud, V P., 517 Supply node, 207 Swart, W., 412 Systematic investigation, T Tanino, M., 517 Teams, Tech reps, 458 Thompson, K M., 359 Time series, 404 Time-series forecasting methods, 404, 407 ARIMA method, 419, 422 averaging forecasting method, 410 exponential smoothing, 414–417 exponential smoothing with trend, 417–421 goal of, 423–424 last-value method, 407–409 moving-average method, 410–413 seasonal effects, 404–406 seasonally adjusted time series, 406–407 shifting distributions problems, 424–425 Time value of money, 76 Toggle, 142 Tomasgard, A., 216 Total profit maximization, 26 Transportation problems, 88, 95–99, 204–205, 211 formulation of problem, 96–97 1002 www.freebookslides.com minimum-cost flow problems, 211 spreadsheet model, 97–99 Transportation service systems, 454 Transshipment node, 207, 216 Transshipment problems, 211 minimum-cost flow problems, 211 Traveling salesman problem, 315–316 Trend, 417 Trend chart, 580 Trend smoothing constant, 420 Trial, 537 Triangular distribution, 553, 569–570 Turnquist, M A., 462 Two-variable problems; see also Product-mix case study graphical method, 25–39 U Uncertain variable cell, 538 uncertainty of competitors’ decisions (case study), 547–551 bidding minimum/maximum values, 547–548 simulation results, 550–551 spreadsheet model, 548–550 Uncertainty of competitors’ decisions (case study), 547–551 bidding minimum/maximum values, 547–548 simulation results, 550–551 spreadsheet model, 548–550 Uniform distribution, 570 chance constraints with, 182–184 Unstable time series, 426 Urbanovich, E., 344 Utility, 336, 367 decision tree and, 373–375 equivalent lottery method, 372 exponential utility function, 375 values of payoffs, 367–368 Utility function for money, U(M), 368, 372–373 estimation of, 375 Utilization factor, 461, 469 V Van Dyke, C., 220 Vander Veen, D J., 462 Variable cost, Villaseñor, J., 76 1003 www.freebookslides.com W Waiting cost, 485 Waiting time in the queue, 455 Waiting time in the system, 455 Ward, J., 206 Wassilak, S G F., 359 Wetherly, J., 517 What-if analysis, 10, 53, 151, 248–250; see also Sensitivity analysis benefits of, 152–153 importance to managers, 152–154 product-mix problem, 154–156 simultaneous changes in objective function coefficients, 162–163 spreadsheet for, 156–158 two-way parameter analysis report, 164–166 Y Ybema, R., 259 Yes-or-no decisions, 243, 246 binary decision variables, 246 crew scheduling, 257–261 interrelationships between decisions, 246–247 project selection, 251–252 site selection, 253–257 Young, E E., 344 Z Zhang, X., 590 1004 www.freebookslides.com 目录 Halftitle The McGraw-Hill/Irwin Series in Operations and Decision Sciences Title Copyright Dedication About the Authors About the Case Writers Preface Acknowledgments Brief Contents Contents Chapter One: Introduction 1.1 The Nature of Management Science 1.2 An Illustration of the Management Science Approach: BreakEven Analysis 1.3 The Relationship Between Analytics and Management Science 1.4 The Impact of Management Science 1.5 Some Special Features of this Book 1.6 Summary Glossary Learning Aids for This Chapter Solved Problem Problems Case 1-1 Keeping Time Chapter Two: Linear Programming: Basic Concepts 2.1 A Case Study: The Wyndor Glass Co Product-Mix Problem 2.2 Formulating the Wyndor Problem on a Spreadsheet 2.3 The Mathematical Model in the Spreadsheet 2.4 The Graphical Method for Solving Two-Variable Problems 1005 10 12 14 22 24 26 36 38 43 52 56 61 64 64 65 65 66 69 72 73 78 86 89 www.freebookslides.com 2.5 Using Excel’s Solver to Solve Linear Programming Problems 2.6 Analytic Solver 2.7 A Minimization Example—The Profit & Gambit Co Advertising-Mix Problem 2.8 Linear Programming from a Broader Perspective 2.9 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 2-1 Auto Assembly Case 2-2 Cutting Cafeteria Costs Case 2-3 Staffing a Call Center Chapter Three: Linear Programming: Formulation and Applications 3.1 A Case Study: The Super Grain Corp Advertising-Mix Problem 3.2 Resource-Allocation Problems 3.3 Cost–Benefit–Trade-Off Problems 3.4 Mixed Problems 3.5 Transportation Problems 3.6 Assignment Problems 3.7 Model Formulation from a Broader Perspective 3.8 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 3-1 Shipping Wood to Market Case 3-2 Capacity Concerns Case 3-3 Fabrics and Fall Fashions Case 3-4 New Frontiers Case 3-5 Assigning Students to Schools Case 3-6 Reclaiming Solid Wastes Case 3-7 Project Pickings 1006 96 103 110 117 119 119 121 121 122 132 134 135 139 141 150 165 173 183 189 194 196 196 197 198 200 219 220 223 226 228 230 231 www.freebookslides.com Chapter Four: The Art of Modeling with Spreadsheets 4.1 A Case Study: The Everglade Golden Years Company Cash Flow Problem 4.2 Overview of the Process of Modeling with Spreadsheets 4.3 Some Guidelines for Building “Good” Spreadsheet Models 4.4 Debugging a Spreadsheet Model 4.5 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 4-1 Prudent Provisions for Pensions 235 237 239 253 263 267 268 268 269 270 275 Chapter Five: What-If Analysis for Linear Programming 277 5.1 The Importance of What-If Analysis to Managers 5.2 Continuing the Wyndor Case Study 5.3 The Effect of Changes in One Objective Function Coefficient 5.4 The Effect of Simultaneous Changes in Objective Function Coefficients 5.5 The Effect of Single Changes in a Constraint 5.6 The Effect of Simultaneous Changes in the Constraints 5.7 Robust Optimization 5.8 Chance Constraints with Analytic Solver 5.9 Summary Glossary Learning Aids for This Chapter Solved Problem Problems Case 5-1 Selling Soap Case 5-2 Controlling Air Pollution Case 5-3 Farm Management Case 5-4 Assigning Students to Schools (Revisited) Chapter Six: Network Optimization Problems 6.1 Minimum-Cost Flow Problems 6.2 A Case Study: The BMZ Co Maximum Flow Problem 6.3 Maximum Flow Problems 1007 279 282 286 296 305 314 320 323 329 331 332 332 333 348 350 353 356 358 360 372 376 www.freebookslides.com 6.4 Shortest Path Problems 6.5 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 6-1 Aiding Allies Case 6-2 Money in Motion Case 6-3 Airline Scheduling Case 6-4 Broadcasting the Olympic Games Chapter Seven: Using Binary Integer Programming to Deal with Yes-or-No Decisions 7.1 A Case Study: The California Manufacturing Co Problem 7.2 Using BIP for Project Selection: The Tazer Corp Problem 7.3 Using BIP for The Selection of Sites for Emergency Services Facilities: The Caliente City Problem 7.4 Using BIP for Crew Scheduling: The Southwestern Airways Problem 7.5 Using Mixed BIP to Deal with Setup Costs for Initiating Production: The Revised Wyndor Problem 7.6 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 7-1 Assigning Art Case 7-2 Stocking Sets Case 7-3 Assigning Students to Schools (Revisited) Case 7-4 Broadcasting the Olympic Games (Revisited) Chapter Eight: Nonlinear Programming 8.1 The Challenges of Nonlinear Programming 8.2 Nonlinear Programming with Decreasing Marginal Returns 8.3 Separable Programming 8.4 Difficult Nonlinear Programming Problems 8.5 Evolutionary Solver and Genetic Algorithms 1008 381 394 395 396 396 398 407 412 414 415 418 420 430 434 439 445 452 452 453 453 455 464 466 469 469 470 473 486 500 515 518 www.freebookslides.com 8.6 Using Analytic Solver to Analyze a Model and Choose a Solving Method 8.7 Summary Glossary Learning Aids for This Chapter Solved Problem Problems Case 8-1 Continuation of the Super Grain Case Study Case 8-2 Savvy Stock Selection Case 8-3 International Investments Chapter Nine: Decision Analysis 9.1 A Case Study: The Goferbroke Company Problem 9.2 Decision Criteria 9.3 Decision Trees 9.4 Sensitivity Analysis with Decision Trees 9.5 Checking Whether to Obtain More Information 9.6 Using New Information to Update the Probabilities 9.7 Using a Decision Tree to Analyze the Problem with a Sequence of Decisions 9.8 Performing Sensitivity Analysis on the Problem with a Sequence of Decisions 9.9 Using Utilities to Better Reflect the Values of Payoffs 9.10 The Practical Application of Decision Analysis 9.11 Summary Glossary Learning Aids for This Chapter Solved Problems Problems Case 9-1 Who Wants to Be a Millionaire? Case 9-2 University Toys and the Business Professor Action Figures Case 9-3 Brainy Business Case 9-4 Smart Steering Support Chapter Ten: Forecasting 527 533 534 535 536 537 546 548 550 553 555 559 566 572 579 582 588 598 603 617 618 619 621 621 623 642 642 643 646 650 10.1 An Overview of Forecasting Techniques 1009 651 www.freebookslides.com 10.2 A Case Study: The Computer Club Warehouse (CCW) Problem 10.3 Applying Time-Series Forecasting Methods to the Case Study 10.4 The Time-Series Forecasting Methods in Perspective 10.5 Causal Forecasting with Linear Regression 10.6 Judgmental Forecasting Methods 10.7 Summary Glossary Summary of Key Formulas Learning Aids for This Chapter Solved Problem Problems Case 10-1 Finagling the Forecasts Chapter Eleven: Queueing Models 654 661 688 693 700 702 703 705 706 706 707 719 725 11.1 Elements of a Queueing Model 11.2 Some Examples of Queueing Systems 11.3 Measures of Performance for Queueing Systems 11.4 A Case Study: The Dupit Corp Problem 11.5 Some Single-Server Queueing Models 11.6 Some Multiple-Server Queueing Models 11.7 Priority Queueing Models 11.8 Some Insights about Designing Queueing Systems 11.9 Economic Analysis of the Number of Servers to Provide 11.10 Summary Glossary Key Symbols Learning Aids for This Chapter Solved Problem Problems Case 11-1 Queueing Quandary Case 11-2 Reducing In-Process Inventory 727 736 739 743 748 761 768 777 785 789 790 792 792 793 794 805 807 Chapter Twelve: Computer Simulation: Basic Concepts 809 12.1 The Essence of Computer Simulation 12.2 A Case Study: Herr Cutter’s Barber Shop (Revisited) 12.3 Analysis of the Case Study 1010 810 826 837 www.freebookslides.com 12.4 Outline of a Major Computer Simulation Study 12.5 Summary Glossary Learning Aids for This Chapter Solved Problem Problems Case 12-1 Planning Planers Case 12-2 Reducing In-Process Inventory (Revisited) Chapter Thirteen: Computer Simulation with Analytic Solver 13.1 A Case Study: Freddie the Newsboy’s Problem 13.2 Bidding for a Construction Project: A Prelude to the Reliable Construction Co Case Study 13.3 Project Management: Revisiting the Reliable Construction Co Case Study 13.4 Financial Risk Analysis: Revisiting the Think-Big Development Co Problem 13.5 Revenue Management in the Travel Industry 13.6 Choosing the Right Distribution 13.7 Decision Making with Parameter Analysis Reports and Trend Charts 13.8 Optimizing with Computer Simulation Using the Solver in Analytic Solver 13.9 Summary Glossary Learning Aids for This Chapter Solved Problem Problems Case 13-1 Action Adventures Case 13-2 Pricing under Pressure Case 13-3 Financial Planning for Retirement Appendix A: Tips for Using Microsoft Excel for Modeling Appendix B: Partial Answers to Selected Problems Index 1011 847 851 852 853 854 854 862 863 864 865 880 887 895 901 909 925 937 948 949 950 950 951 960 962 964 966 974 980 ... may be too much data available to be easily analyzed Dramatic advances in computerized data capture, processing power, data transmission, and storage capabilities are enabling organizations to. .. Information Technology Ninth Edition MANAGEMENT SCIENCE Hillier and Hillier Introduction to Management Science: A Modeling and Case Studies Approach with Spreadsheets Sixth Edition Stevenson and. .. provide a comfortable and familiar environment for formulating and analyzing managerial problems The spreadsheet takes care of applying the necessary mathematics automatically in the background with