In a Linear Programming model with only two decision variables, changing one objective function coefficient

1. Always produces a new set of decision variables for the optimal solution
2. Always changes the slope of the level line
3. Sometimes changes the slope of the constraints
4. Sometimes changes the size of the feasible region
5. Answers a & b
6. Answers a & d

In a maximization Linear Programming model with only two decision variables, if a bounded feasible region exists, and a unique optimal solution exists, then adding an allowable increase in resources to one binding constraint

a. Always increases the objective function value.

b. Always diminishes the objective function value.

c. Always expands the feasible region.

d. Always changes the optimal solution.

e. Answer a & c.

f. Answer a, c & d.

Given any Linear Programming (LP) Model if the feasible region is unbounded

a. The LP model has no redundant constraints

b. The LP optimal solution is unique

c. The level lines will no longer be parallel

d. An optimal solution may exist for a minimization objective function

e. Answer a & b