I am following a course on linear optimization; and unfortunately my brain is already stuck on the first toy example. The example is as follows:
Your company produces Duplo chairs and tables. Profit per chair is 15, profit per table is 20 dollars. We only have 8 small bricks available and 6 big bricks. Each chair needs 1 big brick and 2 small bricks; each table needs 2 big bricks and 2 small bricks. How many chairs and tables should you produce to maximixe profit?
Then, they move on to developing a mathematical model. We introduce two decision variables
- $X_1$: The number of chairs to produce
- $X_2$: the number of tables to produce
To solve this problem, we need to determine the optimal solution of the following linear programming model:
Maximize $15 x_{1}+20 x_{2}$ (Total profit)
Subject to:
$x_{1}+2 x_{2} \leq 6$ (only 6 big bricks)
$2 x_{1}+2 x_{2} \leq 8$ (Only 8 small bricks)
$x_{1} \geq 0, x_{2} \geq 0$ (Produce non-negative quantities)
I get that $15 x_{1}+20 x_{2}$ defines the total profit.
What I don't understand is the following: Why do we express the first two constraints as such? What I don't get is why $x_{1}+2 x_{2} \leq 6$ and $2 x_{1}+2 x_{2} \leq 8$ must hold. For me this reads as the "ingredients" of a chair, and the "ingredients" of a table. Since one chair needs 1 small brick and 2 big bricks, and 1 table needs 2 small bricks and 2 big bricks.
How I see it now, according to these 2 equalities, $x_{1}$ is the number of big bricks and $x_{2}$ is the number of small bricks. $x_{1}$ must be smaller then 6, as we only have 6 big bricks, and $x_{2}$ must be smaller then 8, as we only have 8 small bricks. But that is not how the constraints are specified, and if we specify them in that way (e.g. $x_{1} \leq 6$ and $x_{2} \leq 8$), we lose the power of specifying how many ingredients go into one table or one chair. I don't understand why x1 is the number of chairs, and x2 is the number of tables. How do these constraints work?
I hope I explained my doubts clear enough for someone to help me.