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Lecture Introduction to Management Science with Spreadsheets: Chapter 3 - Stevenson, Ozgur

Chapter 3 "Linear programming: basic concepts and graphical solution", after completing this chapter, you should be able to: Explain what is meant by the terms constrained optimization and linear programming, list the components and the assumptions of linear programming and briefly explain each, name and describe at least three successful applications of linear programming,. | Chapter 3 Linear Programming: Basic Concepts and Graphical Solution Part 2 Introduction to Management Science and Forecasting Learning Objectives Explain what is meant by the terms constrained optimization and linear programming. List the components and the assumptions of linear programming and briefly explain each. Name and describe at least three successful applications of linear programming. Identify the type of problems that can be solved using linear programming. Formulate simple linear programming models. Identify LP problems that are amenable to graphical solutions. After completing this chapter, you should be able to: McGraw-Hill/Irwin 3– Learning Objectives (cont’d) Explain these terms: optimal solution, feasible solution space, corner point, redundant constraint slack, and surplus. Solve two-variable LP problems graphically and interpret your answers. Identify problems that have multiple solutions, problems that have no feasible solutions, unbounded problems, and problems with redundant constraints. After completing this chapter, you should be able to: McGraw-Hill/Irwin 3– Decisions and Linear Programming Constrained optimization Finding the optimal solution to a problem given that certain constraints must be satisfied by the solution. A form of decision making that involves situations in which the set of acceptable solutions is somehow restricted. Recognizes scarcity—the limitations on the availability of physical and human resources. Seeks solutions that are both efficient and feasible in the allocation of resources. McGraw-Hill/Irwin 3– Linear Programming Linear Programming (LP) A family of mathematical techniques (algorithms) that can be used for constrained optimization problems with linear relationships. Graphical method Simplex method Karmakar’s method The problems must involve a single objective, a linear objective function, and linear constraints and have known and constant numerical values. McGraw-Hill/Irwin 3– Example 3–1 . | Chapter 3 Linear Programming: Basic Concepts and Graphical Solution Part 2 Introduction to Management Science and Forecasting Learning Objectives Explain what is meant by the terms constrained optimization and linear programming. List the components and the assumptions of linear programming and briefly explain each. Name and describe at least three successful applications of linear programming. Identify the type of problems that can be solved using linear programming. Formulate simple linear programming models. Identify LP problems that are amenable to graphical solutions. After completing this chapter, you should be able to: McGraw-Hill/Irwin 3– Learning Objectives (cont’d) Explain these terms: optimal solution, feasible solution space, corner point, redundant constraint slack, and surplus. Solve two-variable LP problems graphically and interpret your answers. Identify problems that have multiple solutions, problems that have no feasible solutions, unbounded problems, and .