The Tuna Colada
a Fishing Consortium Anticipates Highly Seasonal Demand

The Tuna Colada
A fishing consortium anticipates highly seasonal demand for their product,yellowtail tuna steaks that can be made into the new drink sensation,the tuna colada.Their estimate of the demand profile appears below.This forecast is based on the demand profile of last year's drink,the okra colada with one key difference.The tuna colada is being positioned as a healthier alternative to eggnog,so demand is expected to climb throughout the planning period with a peak in December.
$$\begin{array} { | c | c | } \hline \text { Month } & \text { Demand Forecast } \\\hline \text { July } & 1,560 \\\hline \text { August } & 2,200 \\\hline \text { September } & 2,850 \\\hline \text { October } & 3,440 \\\hline \text { November } & 4,020 \\\hline \text { December } & 5,280 \\\hline\end{array}$$ The costs for the managerial levers appear in this table.
$\begin{array}{|l|c|}\hline \text { Item } & \text { Cost } \\\hline \text { Materials cost/unit } & \$ 10 \\\hline \text { Inventory holding cost/unit/month } & \$ 4 \\\hline \text { Marginal cost of stockout/unit/month } & \$ 12 \\\hline \text { Hiring and training cost/worker } & \$ 200 \\\hline \text { Layoff cost/worker } & \$ 800 \\\hline \text { Labor hours required/unit } & 3 \\\hline \text { Regular time cost/hour } & \$ 16 \\\hline \text { Over time cost/hour } & \$ 24 \\\hline \text { Period beginning inventory equals } & 0 \\\hline \text { Period ending inventory equals } & 0 \\\hline \text { Marginal subcontracting cost/unit } & \$ 80\\\hline\end{array}$ The base price per tuna colada is $75 and there is currently no promotion,hence,no forward buying,but management is seriously considering different promotional plans.The beginning workforce level is 80 employees.
-Use the Tuna Colada scenario to answer this question.If this problem is to be solved using linear programming,how should the objective function read?

A) Minimize total cost
B) Maximize total revenue
C) Minimize total price
D) Maximize total demand