I've been reading through the book "Linear Programming" - A Concise Introduction by Thomas S.Ferguson and I've came across this idea that:
The function $x_1$ + $x_2$ is constant on lines with slope -1, for example the line $x_1$ + $x_2$ = 1, and as we move this line further from the origin up and to the right, the value of $x_1$ + $x_2$ increases.
Objective function:
$max$ $x_1$ + $x_2$
Set of constraints:
$ x_1 + 2x_2 <= 4 $
$ 4x_1 + 2x_2 <= 12 $
$ -x_1 + x_2 <= 1 $
$ x_1 >= 0 $ and $x_2 >= 0 $
The plot looks like:
Question: Why does the objective function increase on a line with negative slope instead of positive slope. I understand that the function increases as it goes further away from point (0,0) in the ($x_1$, $x_2$) - plane, but I m confused of why should the function increase on a line with negative slope when we can clearly see that every value on that specific line, eg: $x_1$ + $x_2$ = 1 minimizes .

