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Lecture Introduction to Management Science with Spreadsheets: Chapter 10 - Stevenson, Ozgur

Chapter 10 "Multicriteria decision - Making models", after completing this chapter, you should be able to: Describe the type of problems that goal programming is designed to handle, describe the similarities and differences between goal programming and linear programming models, formulate goal programming models,. | Chapter 10 Multicriteria Decision-Making Models Part 2 Deterministic Decision Models Learning Objectives Describe the type of problems that goal programming is designed to handle. Describe the similarities and differences between goal programming and linear programming models. Formulate goal programming models. Solve goal programming models that have two decision variables using a graphical approach. Solve goal programming models using Excel and interpret solutions of goal programming models. After completing this chapter, you should be able to: McGraw-Hill/Irwin 10– Learning Objectives (cont’d) Describe the type of problems that the analytical hierarchy process is designed to handle. Describe how to determine pairwise comparisons. Describe what a consistency check is and calculate a consistency ratio, priority percentage, and priority score for each alternative using AHP. Use Excel to solve analytical hierarchy process problems. Describe and solve scoring model multicriteria decision-making problems. After completing this chapter, you should be able to: McGraw-Hill/Irwin 10– Goal Programming Versus Linear Programming Goal Programming (GP) A variation of linear programming that allows multiple objectives (goals)—soft (goal) constraints or a combination of soft and hard (nongoal) constraints—that can deviate, allowing for tradeoffs in achieving satisficing rather than only optimal solutions. GP models are similar to LP models in that both are formulated under the same requirements and assumptions (e.g., linearity, nonnegativity, certainty). GP uses, like LP, graphical methods to illustrate linear programming concepts. McGraw-Hill/Irwin 10– Figure 10–1 A Plot of a Goal Constraint McGraw-Hill/Irwin 10– Figure 10–2 Designating Priority and Direction McGraw-Hill/Irwin 10– Figure 10–3 Plot of the Hard Constraint and the Feasible Solution Space McGraw-Hill/Irwin 10– Figure 10–4 The Acceptable Region after Adding the First Goal Constraint . | Chapter 10 Multicriteria Decision-Making Models Part 2 Deterministic Decision Models Learning Objectives Describe the type of problems that goal programming is designed to handle. Describe the similarities and differences between goal programming and linear programming models. Formulate goal programming models. Solve goal programming models that have two decision variables using a graphical approach. Solve goal programming models using Excel and interpret solutions of goal programming models. After completing this chapter, you should be able to: McGraw-Hill/Irwin 10– Learning Objectives (cont’d) Describe the type of problems that the analytical hierarchy process is designed to handle. Describe how to determine pairwise comparisons. Describe what a consistency check is and calculate a consistency ratio, priority percentage, and priority score for each alternative using AHP. Use Excel to solve analytical hierarchy process problems. Describe and solve scoring model multicriteria .