Optimization Modeling with Spreadsheets (with CD-ROM) / Edition 1by Kenneth Baker
Pub. Date: 07/15/2005
Publisher: Cengage Learning
Ideal for students in managment and engineering, OPTIMIZATION MODELING WITH SPREADSHEETS (WITH CD-ROM) covers model building and include tutorials on the use of Excel's Solver, and, at a more advanced level, Frontline Systems' Premium Solver. See more details below
Ideal for students in managment and engineering, OPTIMIZATION MODELING WITH SPREADSHEETS (WITH CD-ROM) covers model building and include tutorials on the use of Excel's Solver, and, at a more advanced level, Frontline Systems' Premium Solver.
Table of Contents
1. Introduction to Spreadsheet Modeling for Optimization. Elements of a Model. Spreadsheet Models. A Hierarchy for Analysis. Optimization Software. Using Solver. Summary. Homework. 2. Linear Programming Formulations: Allocation, Covering, and Blending Models. Linear Models. Allocation Models. Blending Models. Modeling Errors in Linear Programming. Summary. Homework. 3. Linear Programming Formulations: Network Models. The Transportation Model. The Assignment Model. The Transshipment Model. Features of Special Network Models. Building Network Models with Balance Equations. General Network Models with Expanding Flows. General Network Models with Transformed Flows. Summary. Homework. 4. Sensitivity Analysis Linear Programs. Sensitivity Analysis Transportation Example. Sensitivity Analysis in the Allocation Example. The Sensitivity Report and the Transportation Example. The Sensitivity Report and the Allocation Example. Degeneracy and Alternative Optima. Patterns in Linear Programming Solutions. Summary. Homework. 5. Linear Programming Formulations: Data Envelopment Analysis. A Graphical Perspective on DEA. An Algebraic Perspective on DEA. A Spreadsheet Model for DEA. Indexing. Finding Reference Sets and HCUs. Assumptions and Limitations of DEA. Summary. Homework. 6. Integer Programming. Using Solver with Integer Requirements. Models with Binary Choice. Models with Qualitative Constraints. The Facility Location Model. The Algorithm for Solving Integer Programs. Summary. Homework. 7. Nonlinear Programming. One-Variable Models. Local Optima and Search for an Optimum. Two-Variable Models. Nonlinear Models with Constraints. Linearizations. Summary. Homework. 8. Heuristic Solutions with the Evolutionary Solver. Features of the Evolutionary Solver. An Illustrative Example: Nonlinear Regression. The Machine-Sequence Problem Revisited. The Traveling Salesperson Problem Revisited. Multi-Machine Scheduling. Two-Dimensional Location. Group Assignment. Summary. Homework. Appendix I. Software. Appendix II. Graphical Methods in Linear Programming. Appendix III. The Simplex Method. Appendix IV. Stochastic Programming.
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