The <em>objective function</em> is the function that you want to optimize: usually minimize in the case of costs, and maximize in the case of revenues or profits.
In this case, you know the <em>profits</em> that a manufacturer earns from two types of <em>bottled coffe drinks</em>: <em>cappuccinos</em> and <em>cafés au lait</em>.
Each bottle of <em>cappuccino earns a profit of $0.40</em> and each bottle of <em>café au lait earns a profit of $0.50</em>.
Then:
using the variable x for the number bottles of cappuccino produced, the profit earned from x bottles is 0.40x, and
using the variable y for the number of bottles of café au lait the produced, the profit earned from y bottles is 0.5y.
The total profit earned, P, is the sum of the profits earned from each type of bottled coffee drinks:
P = 0.40x + 0.50y
That is the <em>objective function</em>, i.e. the function that the manufacturer must try to maximize subject to the corresponding constraints.
