Question: After running solver, we got the sensitivity analysis table as following. Table 1 : Sensitivity Analysis for Tropicsun table [ [ C o l

After running solver, we got the sensitivity analysis table as following.
Table 1: Sensitivity Analysis for Tropicsun
\table[[Coll$D$11,Name,\table[[Final],[Value]],\table[[Shadow],[Price]],\table[[Constraint],[R.H. Side]],\table[[opicsin],[Allowable],[Increase]],\table[[Allowable],[Decrease]]],[,Mt. Dora,275000,48,275000,50000,75000],[,Eustis,400000,30,400000,50000,250000],[$D$13$D$14,Clerment,300000,20,300000,50000,300000],[$0$14$0$15,Ocala,200000,-27,200000,75000,50000],[$D$15,Orlando,550000,0,600000,1E+30,50000],[$D$16,Leesburg,225000,-8,225000,250000,50000]]
Tropicsun has an options to improve their infrastructure. The first option is that increase a capacity of one plant by 50,000 bushels. But it will costs $200,000. Which plant should Tropicsun to choose for capacity increase, or no plant to invest at all, if the transportation cost is $1 per bushel-mile? Justify your conclusion.
Since the shadow price of Ocala capacity is -27(it means if we have one more uni of capacity, our objective function value will go down by $27. This means one mor unit of capacity is $27 saving. And the allowable increase is 75,000 which is greate than 50,000. We can save 50,000$27. Even though we have to pay $200,000 for th capacity increment, we can save more than $200,000 in transportation cost. We ca save by choosing Leesburg plant. However, the saving would be smaller than that the Ocala case.
 After running solver, we got the sensitivity analysis table as following.

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