Linear Programming for Decision Support¶
Example using scipy¶
from scipy.optimize import linprog
obj = [-1, -2]
lhs_ineq = [[ 2, 1], # Red constraint left side
[-4, 5], # Blue constraint left side
[ 1, -2]] # Yellow constraint left side
rhs_ineq = [20, # Red constraint right side
10, # Blue constraint right side
2] # Yellow constraint right side
lhs_eq = [[-1, 5]] # Green constraint left side
rhs_eq = [15] # Green constraint right side
bnd = [(0, float("inf")), # Bounds of x
(0, float("inf"))] # Bounds of y
opt = linprog(c=obj, A_ub=lhs_ineq, b_ub=rhs_ineq,
... A_eq=lhs_eq, b_eq=rhs_eq, bounds=bnd,
... method="revised simplex")
opt
con: array([1.77635684e-15])
fun: -16.818181818181817
message: 'Optimization terminated successfully.'
nit: 3
slack: array([ 0. , 18.18181818, 3.36363636])
status: 0
success: True
x: array([7.72727273, 4.54545455])