def demand_var(info_rv):
pdf = sum([
dirac.f * pacal.PoissonDistr(dirac.a).get_piecewise_pdf()
for dirac in info_rv.get_piecewise_pdf().getDiracs()
])
d_rv = pacal.DiscreteDistr([d.a for d in pdf.getDiracs()],
[d.f for d in pdf.getDiracs()])
return d_rv.var()
def test_case_var(info_states):
weight = 1 / len(info_states)
pdf = sum([
weight * pacal.PoissonDistr(info_state).get_piecewise_pdf()
for info_state in info_states
])
d_rv = pacal.DiscreteDistr([d.a for d in pdf.getDiracs()],
[d.f for d in pdf.getDiracs()])
return d_rv.var()
def usage(self, o):
return pacal.PoissonDistr(o * self.scale, trunk_eps=self.trunk)
merged_fn = "{}_{}.pickle".format(date.today().isoformat(),
configs[0].label)
results.to_pickle(merged_fn)
for config in configs:
os.remove(config.results_fn)
if __name__ == "__main__":
gamma = 0.9
lead_time = 0
horizon = 2
info_state_rvs = [
pacal.ConstDistr(0),
pacal.ConstDistr(0),
#pacal.DiscreteDistr([1, 2, 19, 20], [0.25, 0.25, 0.25, 0.25])
pacal.PoissonDistr(5, trunk_eps=1e-3)
]
holding_cost = 1
backlogging_cost = 10
setup_cost = 5
unit_price = 0
usage_model = PoissonUsageModel(scale=1)
# usage_model = lambda o: pacal.ConstDistr(o)
# usage_model = lambda o: pacal.PoissonDistr(o, trunk_eps=1e-3)
# sage_model = None
model = StationaryOptModel(gamma,
lead_time,
info_state_rvs,
holding_cost,
backlogging_cost,
setup_cost,
def poisson_usage(o):
return pacal.PoissonDistr(o, trunk_eps=1e-3)
rv_2_18 = pacal.DiscreteDistr([2, 18], [0.5, 0.5])
rv_0_20 = pacal.DiscreteDistr([0, 20], [0.5, 0.5])
rv_8_16 = pacal.DiscreteDistr([8, 16], [0.5, 0.5])
test_cases_set_all = {
"E[Demand] 10": rv_10_10,
"E[Demand] 8, 12": rv_8_12,
"E[Demand] 6, 14": rv_6_14,
"E[Demand] 4, 16": rv_4_16,
"E[Demand] 2, 18": rv_2_18,
"E[Demand] 0, 20": rv_0_20
}
info_horizons = [1]
usage_models = {
"Poisson": (lambda o: pacal.PoissonDistr(o, trunk_eps=1e-3), 1)
}
demand_models = {
"E[Demand] 6, 14": rv_6_14,
}
fn = "batch_mdp_results_non_convex_cases_action_inc_v2_20191003_01.pickle"
setup_cost = 50
gamma = 0.9
lead_time = 0
holding_cost = 1
backlogging_cost = 10
unit_price = 0
action_inc = 0.1
rv_10_10 = pacal.DiscreteDistr([10], [1])
rv_8_12 = pacal.DiscreteDistr([8, 12], [0.5, 0.5])
rv_7_13 = pacal.DiscreteDistr([7, 13], [0.5, 0.5])
rv_6_14 = pacal.DiscreteDistr([6, 14], [0.5, 0.5])
rv_5_15 = pacal.DiscreteDistr([5, 15], [0.5, 0.5])
rv_4_16 = pacal.DiscreteDistr([4, 16], [0.5, 0.5])
rv_2_18 = pacal.DiscreteDistr([2, 18], [0.5, 0.5])
rv_0_20 = pacal.DiscreteDistr([0, 20], [0.5, 0.5])
rv_8_16 = pacal.DiscreteDistr([8, 16], [0.5, 0.5])
configs = []
if __name__ == "__main__":
i = 0
for horizon in [1, 2, 3, 4]:
for rv in [rv_4_16, pacal.PoissonDistr(5, trunk_eps=1e-3)]:
s_rv = [rv_0] * horizon + [rv]
s_rv = s_rv if horizon else s_rv + [rv_0]
ns_rv = [s_rv] * 7
ns_config = ns_model.ModelConfig(
gamma=0.9,
lead_time=0,
holding_cost=1,
backlogging_cost=10,
setup_cost=50,
unit_price=0,
usage_model=PoissonUsageModel(scale=1),
ns_info_state_rvs=ns_rv,
horizon=horizon,
label="non_stationary_test",
