Formulate and Solve Optimization Models with Binary Variables and Logical

question 12

Multiple Choice

Formulate and solve optimization models with binary variables and logical constraints. LO2: Use a modern software tool to perform statistical calculations.
Use the table below to answer the following question(s) using the standard Solver. Below is the spreadsheet for a plant location model: $\begin{array}{|l|l|l|l|l|l|l|}\hline &{\text { A }} & \text { B } & \text { C } & \text { D } & \text { E } & \text { F } \\\hline 1 & \begin{array}{l}\text { Plant Location } \\\text { Model }\end{array} & & & & & \\\hline 2 & & & & & & \\\hline 3 & \text { Data } & & & & & \\\hline4&&&\text { Distribution Center }\\\hline 5 & \text { Plant } & \text { Houston } & \text { San Jose } & \text { Jacksonville } & \text { Memphis } & \text { Capacity } \\\hline 6 & \text { Dallas } & \$ 11.80 & \$ 16.48 & \$ 12.35 & \$ 18.56 & 1,300 \\\hline 7 & \text { Atlanta } & \$ 8.54 & \$ 14.65 & \$ 9.58 & \$ 18.25 & 750 \\\hline 8 & \text { Detroit } & \$ 12.89 & \$ 10.78 & \$ 7.85 & \$ 10.28 & 1,400 \\\hline 9 & \text { Baltimore } & \$ 14.36 & \$ 18.95 & \$ 14.61 & \$ 6.64 & 1,300 \\\hline 10 & \text { Demand } & 350 & 450 & 800 & 1,700 & \\\hline 11 & \\\hline 12 & \text { Model } \\\hline 13 & \\\hline 14 & \text { Amount Shipped }&&\text { Distribution Center } \\\hline 15 & \text { Plant } & \text { Houston } & \text { San Jose } & \text { Jack sonville } & \text { Memphis } & \text { Total Shipped } \\\hline 16 & \text { Dallas } & & & & & \\\hline 17 & \text { Atlanta } \\\hline 18 & \text { Detroit } \\\hline 19 & \text { Baltimore } \\\hline 20 & \text { Supply } \\\hline 21 & \\\hline 22 & \text { Total Cost } \\\hline 23 & \$ 0.00 \\\hline\end{array}$
-What is the total amount shipped by the Atlanta plant to the distribution centers?

• A) 600
• B) 1,000
• C) 1,250
• D) 1,300

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Definitions:

SSR

Sum of Squared Residuals; it represents the sum of the squared differences between the observed and predicted values in statistical analysis.

Degrees Of Freedom

The number of values in a calculation that are free to vary while estimating statistical parameters or testing hypotheses.

MSR

Mean Squared Regression, a measure used in statistical analysis to describe the amount of variance explained by a regression model.

MSE

Mean Squared Error, a measure of the average of the squares of the errors—that is, the average squared difference between the estimated values and the actual value.