ECO 550 FINAL EXAM

Topics: Sociology, Psychology, Family, World Wide Web, Marketing, Decision making / Pages: 4 (1177 words) / Published: Sep 21st, 2014
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ECO 550 FINAL EXAM
1. Which of the following could be a linear programming objective function?
2. Which of the following could not be a linear programming problem constraint?
3. Types of integer programming models are _____________.
4. The production manager for Beer etc. produces 2 kinds of beer: light (L) and dark (D). Two resources used to produce beer are malt and wheat. He can obtain at most 4800 oz of malt per week and at most 3200 oz of wheat per week respectively. Each bottle of light beer requires 12 oz of malt and 4 oz of wheat, while a bottle of dark beer uses 8 oz of malt and 8 oz of wheat. Profits for light beer are $2 per bottle, and profits for dark beer are $1 per bottle. If the production manager decides to produce of 0 bottles of light beer and 400 bottles of dark beer, it will result in slack of
5. The reduced cost (shadow price) for a positive decision variable is 0.
6. Decision variables
7. A plant manager is attempting to determine the production schedule of various products to maximize profit. Assume that a machine hour constraint is binding. If the original amount of machine hours available is 200 minutes., and the range of feasibility is from 130 minutes to 340 minutes, providing two additional machine hours will result in the:
8. Decision models are mathematical symbols representing levels of activity.
9. The integer programming model for a transportation problem has constraints for supply at each source and demand at each destination.
10. In a transportation problem, items are allocated from sources to destinations
11. In a media selection problem, the estimated number of customers reached by a given media would generally be specified in the _________________. Even if these media exposure estimates are correct, using media exposure as a surrogate does not lead to maximization of ______________.
12. ____________ solutions are ones that satisfy all the constraints simultaneously.
13. In a

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