def part3():
d = Demand(240, 'M')
rc = RawCosts(50.0, 100.0, 0.01, holding_time_unit='M')
Q = EOQ.optimal_order_quantity(rc, d)
print(Q)
T = EOQ.optimal_cycle_time(rc, d)
print(T)
print(T * 4)
def test_optimal_total_cost_calculates_correctly():
raw_costs = get_raw_costs()
demand = get_demand()
trc = EOQ.optimal_relevant_cost(raw_costs, demand)
expected = trc + raw_costs.unit_cost * demand.quantity
actual = EOQ.optimal_total_cost(raw_costs=raw_costs, demand=demand)
assert expected == actual
def test_optimal_order_quantity_with_zero_holding_cost_returns_demand():
demand = get_demand()
raw_costs = get_raw_costs(holding_rate=0.0)
q_star = EOQ.optimal_order_quantity(raw_costs=raw_costs, demand=demand)
assert q_star == demand.quantity
def qq_06():
c_t = 525
c_e = 1.25
rc = RawCosts(unit_cost=1.00,
ordering_cost=c_t,
holding_cost=c_e,
holding_time_unit='M')
d = Demand(quantity=120, time_unit='M')
Q = EOQ.optimal_order_quantity(raw_costs=rc, demand=d)
print("EOQ: {}".format(Q))
B = 170
L = 1
mu_dl = 30
sigma_dl = 9
inner_value = (B * d.quantity) / (c_e * sigma_dl * Q * sqrt(2 * pi))
print("inner value: {}".format(inner_value))
k = sqrt(2 * log(inner_value))
print("k: {}".format(k))
s = mu_dl + k * sigma_dl
print("s: {}".format(s))
def calc_eoq(row):
cost = row['cost']
demand = row['demand']
rc = RawCosts(unit_cost=cost, ordering_cost=c_t, holding_rate=h)
d = Demand(quantity=demand)
return EOQ.optimal_order_quantity(rc, d)
def test_optimal_cycle_time_calculates_correctly():
import math
demand = get_demand()
raw_costs = get_raw_costs()
t_star = EOQ.optimal_cycle_time(raw_costs=raw_costs, demand=demand)
assert t_star == math.sqrt((2 * raw_costs.ordering_cost) /
(demand.quantity * raw_costs.holding_cost))
def test_optimal_relevant_cost_calculates_correctly():
import math
raw_costs = get_raw_costs()
demand = get_demand()
expected = math.sqrt(2 * raw_costs.ordering_cost * raw_costs.holding_cost *
demand.quantity)
actual = EOQ.optimal_relevant_cost(raw_costs=raw_costs, demand=demand)
assert expected == actual
def test_optimal_order_quantity_calculates_correctly():
import math
demand = get_demand()
raw_costs = get_raw_costs()
q_star = EOQ.optimal_order_quantity(raw_costs=raw_costs, demand=demand)
assert q_star == math.sqrt(2 *
(raw_costs.ordering_cost * demand.quantity) /
raw_costs.holding_cost)
def part01():
sku = '3206-BO1'
item = df.loc[sku]
rc = RawCosts(unit_cost=item['cost'], ordering_cost=c_t, holding_rate=h)
d = Demand(quantity=item['demand'])
Q = EOQ.optimal_order_quantity(rc, d)
print("Q: {}".format(Q))
sigma = item['rmse']
print("sigma: {}".format(sigma))
print("sigma_dl: {}".format(sigma * math.sqrt(1 / 12)))
def part01():
sigma_dl = calc_sigma_dl()
g_k = (0.0211 + 0.0206) / 2 # from table
d = Demand(quantity=D)
rc = RawCosts(unit_cost=c, ordering_cost=c_t, holding_rate=h)
Q = EOQ.optimal_order_quantity(rc, d)
IFR = 1 - ((sigma_dl * g_k) / Q)
print("IFR: {}".format(IFR))
return Q
def part02():
sku = '3206-BO1'
item = df.loc[sku]
cost = item['cost']
demand = item['demand']
rc = RawCosts(unit_cost=cost, ordering_cost=c_t, holding_rate=h)
d = Demand(quantity=demand)
Q = EOQ.optimal_order_quantity(rc, d)
sigma = item['rmse']
sigma_dl = sigma * math.sqrt(1 / 12)
print("sigma_dl * ci: {}".format(sigma_dl * cost))
print("D/Q: {}".format(demand / Q))
print("(D/Q) * (sigma_dl * ci): {}".format((demand / Q) * sigma_dl * cost))
def test_optimal_total_cost_with_missing_raw_costs_raises():
with pytest.raises(ValueError):
EOQ.optimal_total_cost(raw_costs=None, demand=get_demand())
def test_optimal_order_quantity_with_missing_demand_raises():
with pytest.raises(ValueError):
EOQ.optimal_order_quantity(raw_costs=get_raw_costs(), demand=None)
def test_optimal_relevant_cost_with_missing_demand_raises():
with pytest.raises(ValueError):
EOQ.optimal_relevant_cost(raw_costs=get_raw_costs(), demand=None)
def test_optimal_order_quantity_with_missing_raw_scores_raises():
with pytest.raises(ValueError):
EOQ.optimal_order_quantity(raw_costs=None, demand=get_demand())
def test_optimal_cycle_time_with_missing_raw_scores_raises():
with pytest.raises(ValueError):
EOQ.optimal_cycle_time(raw_costs=None, demand=get_demand())
def test_optimal_cycle_time_with_demand_zero_raises():
with pytest.raises(ValueError):
EOQ.optimal_cycle_time(raw_costs=get_raw_costs(),
demand=get_demand(quantity=0))
def test_optimal_cycle_time_with_missing_demand_raises():
with pytest.raises(ValueError):
EOQ.optimal_cycle_time(raw_costs=get_raw_costs(), demand=None)
def test_optimal_cycle_time_with_holding_cost_zero_raises():
with pytest.raises(ValueError):
EOQ.optimal_cycle_time(raw_costs=get_raw_costs(holding_rate=0.0),
demand=get_demand())