An accessible introduction to optimization analysis using spreadsheets Updated and revised, Optimization Modeling with Spreadsheets, Third Edition emphasizes model building skills in optimization analysis. By emphasizing both spreadsheet modeling and optimization tools in the freely available Microsoft® Office Excel® Solver, the book illustrates how to find solutions to real-world optimization problems without needing additional specialized software. The Third Edition includes many practical applications of optimization models as well as a systematic framework that illuminates the common structures found in many successful models. With focused coverage on linear programming, nonlinear programming, integer programming, and heuristic programming, Optimization Modeling with Spreadsheets, Third Edition features: An emphasis on model building using Excel Solver as well as appendices with additional instructions on more advanced packages such as Analytic Solver Platform and OpenSolver Additional space devoted to formulation principles and model building as opposed to algorithms New end-of-chapter homework exercises specifically for novice model builders Presentation of the Sensitivity Toolkit for sensitivity analysis with Excel Solver Classification of problem types to help readers see the broader possibilities for application Specific chapters devoted to network models and data envelopment analysis A companion website with interactive spreadsheets and supplementary homework exercises for additional practice Optimization Modeling with Spreadsheets, Third Edition is an excellent textbook for upper-undergraduate and graduate-level courses that include deterministic models, optimization, spreadsheet modeling, quantitative methods, engineering management, engineering modeling, operations research, and management science. The book is an ideal reference for readers wishing to advance their knowledge of Excel and modeling and is also a useful guide for MBA students and modeling practitioners in business and non-profit sectors interested in spreadsheet optimization.
Intro Title Page Copyright Page Contents PREFACE CHAPTER 1 INTRODUCTION TO SPREADSHEET MODELS FOR OPTIMIZATION 1.1 ELEMENTS OF A MODEL 1.2 SPREADSHEET MODELS 1.3 A HIERARCHY FOR ANALYSIS 1.4 OPTIMIZATION SOFTWARE 1.5 USING SOLVER SUMMARY EXERCISES REFERENCES CHAPTER 2 LINEAR PROGRAMMING: ALLOCATION, COVERING, AND BLENDING MODELS 2.1 LINEAR MODELS 2.1.1 Linear Constraints 2.1.2 Formulation 2.1.3 Layout 2.1.4 Results 2.2 ALLOCATION MODELS 2.2.1 The Product Mix Problem 2.3 COVERING MODELS 2.3.1 The Staff-Scheduling Problem 2.4 BLENDING MODELS 2.5 MODELING ERRORS IN LINEAR PROGRAMMING 2.5.1 Exceptions 2.5.2 Debugging 2.5.3 Logic SUMMARY EXERCISES Case: JetGreen CHAPTER 3 LINEAR PROGRAMMING: NETWORK MODELS 3.1 THE TRANSPORTATION MODEL 3.2 THE ASSIGNMENT MODEL 3.3 THE TRANSSHIPMENT MODEL 3.4 FEATURES OF SPECIAL NETWORK MODELS 3.5 BUILDING NETWORK MODELS WITH BALANCE EQUATIONS 3.6 GENERAL NETWORK MODELS WITH YIELDS 3.6.1 Models with Yield Losses 3.6.2 Models with Yield Gains 3.7 GENERAL NETWORK MODELS WITH TRANSFORMED FLOWS SUMMARY EXERCISES Case: Casey's Famous Roast Beef Case: Hollingsworth Paper Company Production and Distribution Facilities Patterns of Distribution Expansion Proposals CHAPTER 4 SENSITIVITY ANALYSIS IN LINEAR PROGRAMS 4.1 PARAMETER ANALYSIS IN THE TRANSPORTATION EXAMPLE 4.2 PARAMETER ANALYSIS IN THE ALLOCATION EXAMPLE 4.3 THE SENSITIVITY REPORT AND THE TRANSPORTATION EXAMPLE 4.4 THE SENSITIVITY REPORT AND THE ALLOCATION EXAMPLE 4.5 DEGENERACY AND ALTERNATIVE OPTIMA 4.6 PATTERNS IN LINEAR PROGRAMMING SOLUTIONS 4.6.1 The Transportation Model 4.6.2 The Product Portfolio Model 4.6.3 The Investment Model 4.6.4 The Allocation Model 4.6.5 The Refinery Model. SUMMARY EXERCISES Case: Cox Cable and Wire Company Background The Contract The Analysis CHAPTER 5 LINEAR PROGRAMMING: DATA ENVELOPMENT ANALYSIS 5.1 A GRAPHICAL PERSPECTIVE ON DEA 5.2 AN ALGEBRAIC PERSPECTIVE ON DEA 5.3 A SPREADSHEET MODEL FOR DEA 5.4 INDEXING 5.5 REFERENCE SETS AND HCUs 5.6 ASSUMPTIONS AND LIMITATIONS OF DEA SUMMARY EXERCISES Case: Branch Performance at Nashville National Bank Branch Growth at NNB Assessing Branch Productivity Branch Managers Revolt Measuring Branches: Available Techniques The DEA Study CHAPTER 6 INTEGER PROGRAMMING: BINARY-CHOICE MODELS 6.1 USING SOLVER WITH INTEGER REQUIREMENTS 6.2 THE CAPITAL BUDGETING PROBLEM 6.3 SET COVERING 6.4 SET PACKING 6.5 SET PARTITIONING 6.6 PLAYOFF SCHEDULING 6.7 THE ALGORITHM FOR SOLVING INTEGER PROGRAMS SUMMARY EXERCISES Case: Motel Location for Nature's Inn CHAPTER 7 INTEGER PROGRAMMING: LOGICAL CONSTRAINTS 7.1 SIMPLE LOGICAL CONSTRAINTS: EXCLUSIVITY 7.2 LINKING CONSTRAINTS: THE FIXED COST PROBLEM 7.3 LINKING CONSTRAINTS: THE THRESHOLD LEVEL PROBLEM 7.4 LINKING CONSTRAINTS: THE FACILITY LOCATION MODEL 7.4.1 Capacitated Version 7.4.2 Uncapacitated Version 7.5 DISJUNCTIVE CONSTRAINTS: THE MACHINE-SEQUENCING PROBLEM 7.6 TOUR CONSTRAINTS: THE TRAVELING SALESPERSON PROBLEM SUMMARY EXERCISES Case: Hornby Products Company History Alternatives CHAPTER 8 NONLINEAR PROGRAMMING 8.1 ONE-VARIABLE MODELS 8.1.1 An Inventory Example 8.1.2 A Quantity Discount Example 8.2 LOCAL OPTIMA AND THE SEARCH FOR AN OPTIMUM 8.3 TWO-VARIABLE MODELS 8.3.1 Curve Fitting 8.3.2 Two-Dimensional Location 8.4 NONLINEAR MODELS WITH CONSTRAINTS 8.4.1 A Pricing Example 8.4.2 Sensitivity Analysis for Nonlinear Programs. 8.4.3 The Portfolio Optimization Model 8.5 LINEARIZATIONS 8.5.1 Linearizing the Maximum 8.5.2 Linearizing the Absolute Value SUMMARY EXERCISES Case: Delhi Foods CHAPTER 9 HEURISTIC SOLUTIONS WITH THE EVOLUTIONARY SOLVER 9.1 FEATURES OF THE EVOLUTIONARY SOLVER 9.2 AN ILLUSTRATIVE EXAMPLE: NONLINEAR REGRESSION 9.3 THE MACHINE-SEQUENCING PROBLEM REVISITED 9.4 THE TRAVELING SALESPERSON PROBLEM REVISITED 9.5 BUDGET ALLOCATION 9.6 TWO-DIMENSIONAL LOCATION 9.7 LINE BALANCING 9.8 GROUP ASSIGNMENT SUMMARY EXERCISES Case: Colgate Wave (Abridged) Introduction The Study Case Appendix: Market Share Simulation Model (Colgate.xls) Data Calculations Simulation APPENDIX 1 SUPPLEMENTAL FILES AND SOFTWARE A1.1 SUPPLEMENTAL Microsoft® Office Excel® FILES A1.2 ANALYTIC SOLVER PLATFORM FOR EDUCATION SOFTWARE A1.3 OPENSOLVER SOFTWARE APPENDIX 2 GRAPHICAL METHODS FOR LINEAR PROGRAMMING A2.1 AN EXAMPLE A2.2 GENERALITIES APPENDIX 3 THE SIMPLEX METHOD A3.1 AN EXAMPLE A3.2 VARIATIONS OF THE ALGORITHM REFERENCES Index EULA.
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Print version: Baker, Kenneth R. Optimization Modeling with Spreadsheets