302 lines
15 KiB
Python
302 lines
15 KiB
Python
import agentpy as ap
|
|
import math
|
|
|
|
|
|
class FirmAgent(ap.Agent):
|
|
def setup(self, code, name, type_region, revenue_log, a_lst_product):
|
|
self.firm_network = self.model.firm_network
|
|
self.product_network = self.model.product_network
|
|
|
|
self.code = code
|
|
self.name = name
|
|
self.type_region = type_region
|
|
self.revenue_log = revenue_log
|
|
self.a_lst_product = a_lst_product
|
|
self.dct_prod_capacity = {}
|
|
|
|
# self.a_lst_up_product_removed = ap.AgentList(self.model, [])
|
|
# self.a_lst_product_disrupted = ap.AgentList(self.model, [])
|
|
self.a_lst_product_removed = ap.AgentList(self.model, [])
|
|
|
|
self.dct_prod_up_prod_stat = {}
|
|
for prod in a_lst_product:
|
|
self.dct_prod_up_prod_stat[prod] = {
|
|
# Normal / Disrupted / Removed + time step
|
|
'status': [('N', 0)],
|
|
# have or have no supply
|
|
'supply': dict.fromkeys(prod.a_predecessors(), True)
|
|
}
|
|
# print(self.dct_prod_up_prod_stat)
|
|
|
|
self.dct_n_trial_up_prod_removed = {}
|
|
self.dct_cand_alt_supply_up_prod_removed = {}
|
|
self.dct_request_prod_from_firm = {}
|
|
|
|
# para
|
|
self.is_prf_size = self.model.is_prf_size
|
|
self.is_prf_conn = bool(self.p.prf_conn)
|
|
self.str_cap_limit_prob_type = str(self.p.cap_limit_prob_type)
|
|
self.flt_cap_limit_level = float(self.p.cap_limit_level)
|
|
self.flt_diff_new_conn = float(self.p.diff_new_conn)
|
|
self.flt_crit_supplier = float(self.p.crit_supplier)
|
|
|
|
# init extra capacity
|
|
for product in self.a_lst_product:
|
|
# init extra capacity based on discrete uniform distribution
|
|
assert self.str_cap_limit_prob_type in ['uniform', 'normal'], \
|
|
"cap_limit_prob_type other than uniform, normal"
|
|
if self.str_cap_limit_prob_type == 'uniform':
|
|
extra_cap_mean = \
|
|
self.revenue_log / self.flt_cap_limit_level
|
|
extra_cap = self.model.nprandom.integers(extra_cap_mean-2,
|
|
extra_cap_mean+2)
|
|
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
|
# print(firm_agent.name, extra_cap)
|
|
self.dct_prod_capacity[product] = extra_cap
|
|
elif self.str_cap_limit_prob_type == 'normal':
|
|
extra_cap_mean = \
|
|
self.revenue_log / self.flt_cap_limit_level
|
|
extra_cap = self.model.nprandom.normal(extra_cap_mean, 1)
|
|
extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
|
|
# print(firm_agent.name, extra_cap)
|
|
self.dct_prod_capacity[product] = extra_cap
|
|
|
|
def remove_edge_to_cus_remove_cus_up_prod(self, remove_product):
|
|
lst_out_edge = list(
|
|
self.firm_network.graph.out_edges(
|
|
self.firm_network.positions[self], keys=True, data='Product'))
|
|
for n1, n2, key, product_code in lst_out_edge:
|
|
if product_code == remove_product.code:
|
|
# remove edge
|
|
self.firm_network.graph.remove_edge(n1, n2, key)
|
|
|
|
# remove customer up product conditionally
|
|
customer = ap.AgentIter(self.model, n2).to_list()[0]
|
|
lst_in_edge = list(
|
|
self.firm_network.graph.in_edges(n2,
|
|
keys=True,
|
|
data='Product'))
|
|
lst_select_in_edge = [
|
|
edge for edge in lst_in_edge
|
|
if edge[-1] == remove_product.code
|
|
]
|
|
prod_remove = math.exp(-1 * self.flt_crit_supplier *
|
|
len(lst_select_in_edge))
|
|
if self.model.nprandom.choice([True, False],
|
|
p=[prod_remove,
|
|
1 - prod_remove]):
|
|
# if remove_product not in \
|
|
# customer.a_lst_up_product_removed:
|
|
# customer.a_lst_up_product_removed.append(
|
|
# remove_product)
|
|
# customer.dct_n_trial_up_prod_removed[
|
|
# remove_product] = 0
|
|
|
|
for prod in customer.dct_prod_up_prod_stat.keys():
|
|
if remove_product in \
|
|
customer.dct_prod_up_prod_stat[
|
|
prod]['supply'].keys():
|
|
customer.dct_prod_up_prod_stat[
|
|
prod]['supply'][remove_product] = False
|
|
customer.dct_prod_up_prod_stat[
|
|
prod]['status'].append(('D', self.model.t))
|
|
|
|
customer.dct_n_trial_up_prod_removed[
|
|
remove_product] = 0
|
|
print(self.name, remove_product.code, 'affect',
|
|
customer.name, prod.code)
|
|
# print(customer.dct_prod_up_prod_stat)
|
|
|
|
def seek_alt_supply(self, product):
|
|
# para product is the product that self is seeking
|
|
# for product in self.a_lst_up_product_removed:
|
|
print(f"{self.name} seek alt supply for {product.code}")
|
|
if self.dct_n_trial_up_prod_removed[
|
|
product] <= self.model.int_n_max_trial:
|
|
if self.dct_n_trial_up_prod_removed[product] == 0:
|
|
# select a list of candidate firm that has the product
|
|
self.dct_cand_alt_supply_up_prod_removed[product] = \
|
|
self.model.a_lst_total_firms.select([
|
|
product in firm.a_lst_product
|
|
and product not in firm.a_lst_product_removed
|
|
for firm in self.model.a_lst_total_firms
|
|
])
|
|
if self.dct_cand_alt_supply_up_prod_removed[product]:
|
|
# select based on connection
|
|
lst_firm_connect = []
|
|
if self.is_prf_conn:
|
|
for firm in \
|
|
self.dct_cand_alt_supply_up_prod_removed[product]:
|
|
out_edges = self.model.firm_network.graph.out_edges(
|
|
self.model.firm_network.positions[firm], keys=True)
|
|
in_edges = self.model.firm_network.graph.in_edges(
|
|
self.model.firm_network.positions[firm], keys=True)
|
|
lst_adj_firm = []
|
|
lst_adj_firm += \
|
|
[ap.AgentIter(self.model, edge[1]).to_list()[
|
|
0].code for edge in out_edges]
|
|
lst_adj_firm += \
|
|
[ap.AgentIter(self.model, edge[0]).to_list()[
|
|
0].code for edge in in_edges]
|
|
if self.code in lst_adj_firm:
|
|
lst_firm_connect.append(firm)
|
|
if len(lst_firm_connect) == 0:
|
|
# select based on size or not
|
|
if self.is_prf_size:
|
|
lst_size = \
|
|
[size for size in
|
|
self.dct_cand_alt_supply_up_prod_removed[
|
|
product].revenue_log]
|
|
lst_prob = [size / sum(lst_size)
|
|
for size in lst_size]
|
|
select_alt_supply = self.model.nprandom.choice(
|
|
self.dct_cand_alt_supply_up_prod_removed[product],
|
|
p=lst_prob)
|
|
else:
|
|
select_alt_supply = self.model.nprandom.choice(
|
|
self.dct_cand_alt_supply_up_prod_removed[product])
|
|
elif len(lst_firm_connect) > 0:
|
|
# select based on size of connected firm or not
|
|
if self.is_prf_size:
|
|
lst_firm_size = \
|
|
[firm.revenue_log for firm in lst_firm_connect]
|
|
lst_prob = \
|
|
[size / sum(lst_firm_size)
|
|
for size in lst_firm_size]
|
|
select_alt_supply = \
|
|
self.model.nprandom.choice(lst_firm_connect,
|
|
p=lst_prob)
|
|
else:
|
|
select_alt_supply = \
|
|
self.model.nprandom.choice(lst_firm_connect)
|
|
print(
|
|
f"{self.name} selct alt supply for {product.code} "
|
|
f"from {select_alt_supply.name}"
|
|
)
|
|
assert product in select_alt_supply.a_lst_product, \
|
|
f"{select_alt_supply} \
|
|
does not produce requested product {product}"
|
|
|
|
if product in select_alt_supply.dct_request_prod_from_firm.\
|
|
keys():
|
|
select_alt_supply.dct_request_prod_from_firm[
|
|
product].append(self)
|
|
else:
|
|
select_alt_supply.dct_request_prod_from_firm[product] = [
|
|
self
|
|
]
|
|
print(
|
|
select_alt_supply.name, 'dct_request_prod_from_firm', {
|
|
key.code: [v.name for v in value]
|
|
for key, value in
|
|
select_alt_supply.dct_request_prod_from_firm.items()
|
|
})
|
|
|
|
self.dct_n_trial_up_prod_removed[product] += 1
|
|
|
|
def handle_request(self):
|
|
print(self.name, 'handle_request')
|
|
for product, lst_firm in self.dct_request_prod_from_firm.items():
|
|
if self.dct_prod_capacity[product] > 0:
|
|
if len(lst_firm) == 0:
|
|
continue
|
|
elif len(lst_firm) == 1:
|
|
self.accept_request(lst_firm[0], product)
|
|
elif len(lst_firm) > 1:
|
|
# handling based on connection
|
|
lst_firm_connect = []
|
|
if self.is_prf_conn:
|
|
for firm in lst_firm:
|
|
out_edges = \
|
|
self.model.firm_network.graph.out_edges(
|
|
self.model.firm_network.positions[firm],
|
|
keys=True)
|
|
in_edges = \
|
|
self.model.firm_network.graph.in_edges(
|
|
self.model.firm_network.positions[firm],
|
|
keys=True)
|
|
lst_adj_firm = []
|
|
lst_adj_firm += \
|
|
[ap.AgentIter(self.model, edge[1]).to_list()[
|
|
0].code for edge in out_edges]
|
|
lst_adj_firm += \
|
|
[ap.AgentIter(self.model, edge[0]).to_list()[
|
|
0].code for edge in in_edges]
|
|
if self.code in lst_adj_firm:
|
|
lst_firm_connect.append(firm)
|
|
if len(lst_firm_connect) == 0:
|
|
# handling based on size or not
|
|
if self.is_prf_size:
|
|
lst_firm_size = \
|
|
[firm.revenue_log for firm in lst_firm]
|
|
lst_prob = \
|
|
[size / sum(lst_firm_size)
|
|
for size in lst_firm_size]
|
|
select_customer = \
|
|
self.model.nprandom.choice(lst_firm,
|
|
p=lst_prob)
|
|
else:
|
|
select_customer = \
|
|
self.model.nprandom.choice(lst_firm)
|
|
self.accept_request(select_customer, product)
|
|
elif len(lst_firm_connect) > 0:
|
|
# handling based on size of connected firm or not
|
|
if self.is_prf_size:
|
|
lst_firm_size = \
|
|
[firm.revenue_log for firm in lst_firm_connect]
|
|
lst_prob = \
|
|
[size / sum(lst_firm_size)
|
|
for size in lst_firm_size]
|
|
select_customer = \
|
|
self.model.nprandom.choice(lst_firm_connect,
|
|
p=lst_prob)
|
|
else:
|
|
select_customer = \
|
|
self.model.nprandom.choice(lst_firm_connect)
|
|
self.accept_request(select_customer, product)
|
|
|
|
def accept_request(self, down_firm, product):
|
|
# para product is the product that self is selling
|
|
prod_accept = self.flt_diff_new_conn
|
|
if self.model.nprandom.choice([True, False],
|
|
p=[prod_accept, 1 - prod_accept]):
|
|
self.firm_network.graph.add_edges_from([
|
|
(self.firm_network.positions[self],
|
|
self.firm_network.positions[down_firm], {
|
|
'Product': product.code
|
|
})
|
|
])
|
|
self.dct_prod_capacity[product] -= 1
|
|
self.dct_request_prod_from_firm[product].remove(down_firm)
|
|
# down_firm.a_lst_up_product_removed.remove(product)
|
|
|
|
for prod in down_firm.dct_prod_up_prod_stat.keys():
|
|
if product in down_firm.dct_prod_up_prod_stat[
|
|
prod]['supply'].keys():
|
|
down_firm.dct_prod_up_prod_stat[
|
|
prod]['supply'][product] = True
|
|
down_firm.dct_prod_up_prod_stat[
|
|
prod]['status'].append(('N', self.model.t))
|
|
# print(down_firm.dct_prod_up_prod_stat)
|
|
del down_firm.dct_n_trial_up_prod_removed[product]
|
|
del down_firm.dct_cand_alt_supply_up_prod_removed[product]
|
|
|
|
print(
|
|
f"{self.name} accept {product.code} request "
|
|
f"from {down_firm.name}"
|
|
)
|
|
else:
|
|
down_firm.dct_cand_alt_supply_up_prod_removed[product].remove(self)
|
|
|
|
def clean_before_trial(self):
|
|
self.dct_request_prod_from_firm = {}
|
|
|
|
def clean_before_time_step(self):
|
|
self.dct_n_trial_up_prod_removed = \
|
|
dict.fromkeys(self.dct_n_trial_up_prod_removed.keys(), 0)
|
|
self.dct_cand_alt_supply_up_prod_removed = {}
|
|
# self.a_lst_up_product_removed = ap.AgentList(self.model, [])
|
|
|
|
def get_firm_network_node(self):
|
|
return self.firm_network.positions[self]
|