Question

1. Are Linear Programming (LP) models deterministic, stochastic or something else? Explain.
2. What are some common properties of LP models?
3. What is the three-step process for solving LP models?
4. How are constraints modeled graphically?
5. What is the corner point property? How is it useful in solving LP models?

Thank you!

Answer 1

1) What are some common properties of LP models?

Ans. 1) Seek t minimize or maximize

2) Include "constraints"or limitations.

3) There must be alternatives available.

4) All equations are linear.

2) What is the three-step process for solving LP models?

1. Understand the problem

2. Describe the objective.

3. Define the decision variables.

4. Write the objective function.

5. Describe the constraints.

6. Write the constraints in terms of the decision variables.

7. Add the non-negativity constraints.

3) How are constraints modeled graphically?

Ans. Express each constraint in terms of the equation i.e replaces inequality sign in each constraint by an equality sign. Assign an arbitrary value to the decision variables x1 and x2 to get plotting points. Plot these points on the graph and join them by a straight line.

4) What is the corner point property? How is it useful in solving the LP model?

Ans- What is the corner point property- A vertex of the feasible region. Not every intersection of lines is a corner point. The corner points only occur at a vertex of the feasible region. If there is going to be an optimal solution to a linear programming problem. It will occur at one of more corner points, or on a line segment between two corner points.

How is it useful in solving the LP model?

The corner point properties are the vertices of the feasible region. Once you have the graph of the system of linear inequalities, then you can look at the graph and easily tell where the corner points ate. You may need to solve a system of linear equations to find some of the coordinates of the points in the middle.