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import numpy as np
from models.solvers.ortools.ortools_base import ORToolsBase
class ORToolsTSPTW(ORToolsBase):
def __init__(self, large_value=1e+6, scaling=False):
super().__init__(large_value, scaling)
def scaling_feats(self, node_feats):
return {
key: (node_feat * self.large_value).astype(np.int64)
if key in ("coords", "time_window") else
node_feat
for key, node_feat in node_feats.items()
}
def add_constraints(self, routing, transit_callback_index, manager, data, node_feats):
"""
Adding time-window contraints
Paramters
---------
node_feats: dict
"""
time_window = node_feats["time_window"]
end_time = time_window[0, 1].item()
routing.AddDimension(
transit_callback_index,
end_time, # max_wait_time (No limit)
end_time, # end_time
False,
"Time"
)
time_dimension = routing.GetDimensionOrDie("Time")
# penalty
for i in range(len(data['distance_matrix'])):
index = manager.NodeToIndex(i)
routing.AddDisjunction([index], 100000000)
# set time window
for i in range(len(data['distance_matrix'])):
index = manager.NodeToIndex(i)
start = time_window[i, 0]
end = time_window[i, 1]
time_dimension.CumulVar(index).SetRange(int(start), int(end)) |