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MidtermExamAKey

# MidtermExamAKey - OSCM 230 MIDTERM EXAM A(Key SPRING 2011...

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1 OSCM 230 MIDTERM EXAM A (Key) SPRING 2011 PROFESSOR DONG 1 Hour and 20 Minutes Question Score True/False (10 pts) Multiple Choice(10 pts) 1. Excel (10 pts) 2. LP Formulation (18 pts) 3. LP Formulation (12 pts) 4. Integer LP Formulation (15 pts) 5. Sensitivity) (25 pts) Bonus (2 pts) Total NAME_________________

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2 True/False (10 pts) 1. As long as a solution satisfies one constraint in a linear programming problem it is called a feasible solution of the problem. True False 2. A nice property of the quadratic programming model is that the local maximal is also the global maximal. True False 3. For a cost minimization integer linear programming problem, the objective function value of its LP relaxation always provides a lower bound on the objective function value of the original problem. True False 4. A convex programming model should have an objective of maximizing the value of a convex function. True False 5. In LP, if the change of the right hand side constant is within the allowable range for that constraint, then the optimal solution will not change. True False Multiple choices (10 pts) 1. In a quadratic programming model with n decision variables, ( x 1 , x 2 , …, x n ), the objective function cannot include terms of the form : a. 2 j x b. i j x x c. 2 i j x x d. 3 2. What should we do if Solver’s message is “Solver could not find a feasible solution”? a. Check objective function to see if “MAX” should be “MIN,” or “MIN” should be “MAX” b. Check if we miss any constraints c. Check if we have too many constraints or conflicting constraints d. Check if we define too many decision variables