a snippet that shows the implementation of the qp appx

snippet _qp_model.py

from helpers.mip import get_quadratic_appx
# get a new variable that represents u^2 = qa_u

qa_u = {}
for i in stores:
    for t in days: 
        qa_u[(i,t)] = get_quadratic_appx(model = mdl, 
                                         var = u[(i,t)], 
                                         id_name = 'qpu_{}_{}'.format(i,t),
                                         min_interval = 0, # lower value where we estimate that u will be moving 
                                         max_interval = 100, # higher value where we estimate that u will be moving 
                                         num_linspace = 5 # number of points of discretization or interest
                                         )

mdl.objective = mip.xsum(qa_u[(i,t)] for i in stores for t in days)