tailieunhanh - Lecture Introduction to Management Science with Spreadsheets: Chapter 4 - Stevenson, Ozgur

Chapter 4 "Applications and solutions of linear programming", after completing this chapter, you should be able to: Formulate linear programming problems with different objectives, set up constraints that have unique structures, translate statements into constraint formulas, utilize excel to solve a variety of linear programming problems,. | Chapter 4 Applications and Solutions of Linear Programming Part 2 Introduction to Management Science and Forecasting Learning Objectives Formulate linear programming problems with different objectives. Set up constraints that have unique structures. Translate statements into constraint formulas. Utilize Excel to solve a variety of linear programming problems. Interpret the Excel output of linear programming problems. Make managerial conclusions based on computer (Excel) output. Explain at least two applications of linear programming. After completing this chapter, you should be able to: McGraw-Hill/Irwin 4– Elements of Linear Programming Issues in formulating problems Degree of simplification of the real-world problem Violation of the assumptions of linear programming (additivity, divisibility, certainty, and proportionality) Linear programming problems may include: Different types of decision variables definitions Different types of constraints Different types of objective functions. McGraw-Hill/Irwin 4– Example 4-1 Product-Mix Problem The Style and Comfort Furniture Manufacturing Company wishes to determine its production schedule for the next quarter. The company produces four types of furniture, including sofas, love seats, recliners, and coffee tables. The profit contribution from selling one sofa is $120, one love seat is $105, one recliner is $150, and one coffee table is $73. The quarterly production budget is set at $180,000. Each unit of a sofa, love seat, recliner, and coffee table costs $400, $300, $500, and $150, respectively. The sales forecasts indicate that the potential sales volume is limited to 200 units of sofas, 150 units of love seats, 100 units of recliners, and 400 units of coffee tables. There are an aggregate of 800 machine hours available and 1,200 labor hours available. Table 4-1 summarizes the number of machine hours and the number of labor hours required per unit of each product. McGraw-Hill/Irwin 4– Table 4–1 Per Unit . | Chapter 4 Applications and Solutions of Linear Programming Part 2 Introduction to Management Science and Forecasting Learning Objectives Formulate linear programming problems with different objectives. Set up constraints that have unique structures. Translate statements into constraint formulas. Utilize Excel to solve a variety of linear programming problems. Interpret the Excel output of linear programming problems. Make managerial conclusions based on computer (Excel) output. Explain at least two applications of linear programming. After completing this chapter, you should be able to: McGraw-Hill/Irwin 4– Elements of Linear Programming Issues in formulating problems Degree of simplification of the real-world problem Violation of the assumptions of linear programming (additivity, divisibility, certainty, and proportionality) Linear programming problems may include: Different types of decision variables definitions Different types of constraints Different types of objective .

• Quản trị kinh doanh
• Management science
• Management science with spreadsheets
• Deterministic decision models
• Probabilistic decision models
• Linear programming
• Marketing applications
• Applications of management science
• Excel spreadsheets
• Management thought
• Evolution of management thought
• Ideas in management
• Management theory
• Systems in management
• Production management
• Forecasting process
• Qualitative forecasts
• Graphical solution
• Simplex method
• Sensitivity analysis
• Transportation method
• Solving transportation problems
• Integer programming
• Integer programming problems
• Solving integer programming
• Nonlinear programming
• Network optimization models
• Differential arithmetic
• Multicriteria decision
• Making models
• Decision theory
• Decision making
• Waiting line models
• Poisson distribution
• Fixed Interval simulations
• Discrete simulations
• An introduction to management science
• Advanced linear programming applications
• Integer linear programming
• Markov processes
• Nonlinear optimization models
• Inventory models
• Decision analysis