Let's run an optimization problem on Streamlit ❤️
In the top of this simple app, one can choose the type of objective function we would like to minimize, which is either a linear
(will be solved with Pyomo) one, or a nonlinear
(will be solved using GEKKO) one.
Since this is a very simple example, we stick to the following objective functions:
-
linear
:$F(x) = c_1x_1 + c_2x_2$ -
nonlinear
:$F(x) = c_1x_1^2 + c_2x_2$
The constraints are the following (equal in both cases):
$f_1: \quad a_1x_1 + a_2x_2 \geq b_1$ $f_2: \quad x_2 \geq b_2$ $f_3: \quad x_i \geq 0, \quad i=1,2$
The app is stored on the publicly available Streamlit cloud here ⛅, where you can choose values for the paramaters