Exam 2: An Introduction to Linear Programming

Only binding constraints form the shape (boundaries) of the feasible region.

Because the dual price represents the improvement in the value of the optimal solution per unit increase in right-hand-side, a dual price cannot be negative.

Does the following linear programming problem exhibit infeasibility, unboundedness, or alternate optimal solutions? Explain. Min 1X + 1Y s.t. 5X + 3Y ≤ 30 3X + 4Y ≥ 36 Y ≤ 7 X , Y ≥ 0

Find the complete optimal solution to this linear programming problem. Min 5X + 6Y s.t. 3X + Y ≥ 15 X + 2Y ≥ 12 3X + 2Y ≥ 24 X , Y ≥ 0

It is possible to have exactly two optimal solutions to a linear programming problem.

Muir Manufacturing produces two popular grades of commercial carpeting among its many other products. In the coming production period, Muir needs to decide how many rolls of each grade should be produced in order to maximize profit. Each roll of Grade X carpet uses 50 units of synthetic fiber, requires 25 hours of production time, and needs 20 units of foam backing. Each roll of Grade Y carpet uses 40 units of synthetic fiber, requires 28 hours of production time, and needs 15 units of foam backing. The profit per roll of Grade X carpet is $200 and the profit per roll of Grade Y carpet is $160. In the coming production period, Muir has 3000 units of synthetic fiber available for use. Workers have been scheduled to provide at least 1800 hours of production time (overtime is a possibility). The company has 1500 units of foam backing available for use. Develop and solve a linear programming model for this problem.