mdl.add_constraint(
(mdl.sum(Y[(c,d)]
for c in range(0,C)
for d in range(0,D)) <= E_c.sum() * PMS.b)
)#33
mdl.add_constraints(
(mdl.sum(Y[(c,d)] for c in range(0,C)) <= E_c.sum() * PMS.k )
for d in range(0,D))#34
return mdl, Y
if __name__ == '__main__':
#case = Case({"C":5,"U":200,"H":3, "D":7, "I":3, "P":3})#3
case = Case({"C":10,"U":2000,"H":3, "D":7, "I":3, "P":3})#6
solution = Solution("Many")
PMS:Parameters = solution.generate_parameters(case, None)
C = case.arguments["C"] # number of campaigns
U = case.arguments["U"] # number of customers.
H = case.arguments["H"] # number of channels.
D = case.arguments["D"] # number of planning days.
I = case.arguments["I"] # number of planning days.
mdl, Y = start_model(C, D, I, PMS)
# print(mdl.objective_expr)
# for consts in mdl.iter_constraints():
# print(consts)
E_c = PMS.e_cu.sum(axis=1)
L_c = (PMS.l_c*E_c)
E_d_i = (PMS.q_ic @ E_c.reshape(C,1)).reshape(I,)
#!/usr/bin/env python
"""
This script auto-generates a sample on-disk dataset for testing.
"""
import numpy as np
import os
import pandas as pd
import xarray as xr
from experiment import Experiment, Case
PATH_TO_DATA = os.path.join(os.path.dirname(__file__), "sample")
cases = [
Case("param1", "Parameter 1", ["a", "b", "c"]),
Case("param2", "Parameter 2", [1, 2, 3]),
Case("param3", "Parameter 3", ["alpha", "beta"]),
]
exp = Experiment(
"sample", cases, timeseries=True, data_dir=PATH_TO_DATA,
case_path="{param1}_{param2}",
output_prefix="{param1}.{param2}.{param3}.",
output_suffix=".tape.nc", validate_data=False
)
VARS = ["temp", "pres", "precip"]
def _make_dataset(varname, seed=None, **var_kws):
rs = np.random.RandomState(seed)
if __name__ == '__main__':
cases = [
# Case({"C":2,"U":100,"H":3, "D":7, "I":3, "P":3}),#1
# Case({"C":5,"U":100,"H":3, "D":7, "I":3, "P":3}),#2
# Case({"C":5,"U":200,"H":3, "D":7, "I":3, "P":3}),#3
# Case({"C":5,"U":1000,"H":3, "D":7, "I":3, "P":3}),#4
# Case({"C":10,"U":1000,"H":3, "D":7, "I":3, "P":3}),#5
# Case({"C":10,"U":2000,"H":3, "D":7, "I":3, "P":3}),#6
# Case({"C":10,"U":3000,"H":3, "D":7, "I":3, "P":3}),#7
# Case({"C":10,"U":4000,"H":3, "D":7, "I":3, "P":3}),#8
# Case({"C":10,"U":5000,"H":3, "D":7, "I":3, "P":3}),#9
# Case({"C":20,"U":10000,"H":3, "D":7, "I":3, "P":3}),#10
Case({
"C": 20,
"U": 20000,
"H": 3,
"D": 7,
"I": 3,
"P": 3
}), #11
# Case({"C":20,"U":30000,"H":3, "D":7, "I":3, "P":3}),
# Case({"C":20,"U":40000,"H":3, "D":7, "I":3, "P":3}),
# Case({"C":20,"U":50000,"H":3, "D":7, "I":3, "P":3})
]
expr = Experiment(cases)
solutions = expr.run_cases_with(LpRelSolution())
for solution in solutions:
print(solution)
#
#<case: {'C': 5, 'U': 100, 'H': 3, 'D': 7, 'I': 3, 'P': 3}, value: 12180, duration: 1.5658>
#<case: {'C': 10, 'U': 1000, 'H': 3, 'D': 7, 'I': 3, 'P': 3}, value: 341667, duration: 29.2164>