348 lines
17 KiB
Python
348 lines
17 KiB
Python
from mesa import Agent
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class FirmAgent(Agent):
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def __init__(self, unique_id, model, type_region, revenue_log, n_equip_c, a_lst_product,
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production_output, demand_quantity, c_price, R, P, C):
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# 调用超类的 __init__ 方法
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super().__init__(unique_id, model)
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# 初始化模型中的网络引用
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self.firm_network = self.model.firm_network
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self.product_network = self.model.product_network
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# 初始化代理自身的属性
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self.type_region = type_region
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self.size_stat = []
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self.dct_prod_up_prod_stat = {}
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self.dct_prod_capacity = {}
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# 企业涉及的产业
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self.indus_i = a_lst_product
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# 各资源库存信息，库存资源，库存量
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self.R = R
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# 包括库存时间的值 方便后面统计
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self.R1 = {0: R}
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# 设备资产信息，持有设备，设备数量， 增加 设备残值 [[1,2,3],[] ]
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self.C = C
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# 包括设备时间步的值
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self.C1 = {0: C}
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# 复制一份
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self.C0 = C
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# 产品库存信息 库存产品，库存量 ID 数量
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self.P = P
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# 包括 产品时间
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self.P1={0:P}
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# 企业i的供应商
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self.upper_i = [u for u, v in self.firm_network.in_edges(self.unique_id)]
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# 企业i的客户
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self.downer_i = [u for u, v in self.firm_network.out_edges(self.unique_id)]
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# 设备c的数量 （总量） 使用这个来判断设备数量
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self.n_equip_c = n_equip_c
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# 设备c产量 更具设备量进行估算
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self.c_yield = production_output
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# 消耗材料量 根据设备量进行估算
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self.c_consumption = demand_quantity
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# 设备c购买价格（初始值）
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self.c_price = c_price
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# 资源r补货库存阈值
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self.s_r = 40
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self.S_r = 120
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# 设备补货阙值 可选
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# self.ss_r = 70
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# 每一个周期步减少残值：x
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self.x = 20
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# 试验中的参数
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self.dct_n_trial_up_prod_disrupted = {}
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self.dct_cand_alt_supp_up_prod_disrupted = {}
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self.dct_request_prod_from_firm = {}
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# 外部变量
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self.is_prf_size = self.model.is_prf_size
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self.is_prf_conn = bool(self.model.prf_conn)
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self.str_cap_limit_prob_type = str(self.model.cap_limit_prob_type)
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self.flt_cap_limit_level = float(self.model.cap_limit_level)
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self.flt_diff_new_conn = float(self.model.diff_new_conn)
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# 初始化 size_stat
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self.size_stat.append((revenue_log, 0))
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# 初始化 dct_prod_up_prod_stat
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for prod in a_lst_product:
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self.dct_prod_up_prod_stat[prod] = {
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'p_stat': [('N', 0)],
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's_stat': {up_prod: {'stat': True, 'set_disrupt_firm': set()}
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for up_prod in prod.a_predecessors()}
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}
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# 初始化额外容量 (dct_prod_capacity)
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for product in a_lst_product:
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assert self.str_cap_limit_prob_type in ['uniform', 'normal'], \
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"cap_limit_prob_type must be either 'uniform' or 'normal'"
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extra_cap_mean = self.size_stat[0][0] / self.flt_cap_limit_level
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if self.str_cap_limit_prob_type == 'uniform':
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extra_cap = self.model.random.uniform(extra_cap_mean - 2, extra_cap_mean + 2)
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extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
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elif self.str_cap_limit_prob_type == 'normal':
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extra_cap = self.model.random.normalvariate(extra_cap_mean, 1)
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extra_cap = 0 if round(extra_cap) < 0 else round(extra_cap)
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self.dct_prod_capacity[product] = extra_cap
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def remove_edge_to_cus(self, disrupted_prod):
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# parameter disrupted_prod is the product that self got disrupted
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lst_out_edge = list(
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self.firm_network.out_edges(
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self.unique_id, keys=True, data='Product'))
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for n1, n2, key, product_code in lst_out_edge:
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if product_code == disrupted_prod.unique_id:
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# update customer up product supplier status
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customer = next(agent for agent in self.model.company_agents if agent.unique_id == n2)
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for prod in customer.dct_prod_up_prod_stat.keys():
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if disrupted_prod in customer.dct_prod_up_prod_stat[prod]['s_stat'].keys():
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customer.dct_prod_up_prod_stat[prod]['s_stat'][disrupted_prod][
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'set_disrupt_firm'].add(self)
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# print(f"{self.name} disrupt {customer.name}'s "
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# f"{prod.code} due to {disrupted_prod.code}")
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# remove edge to customer
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self.firm_network.remove_edge(n1, n2, key)
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def disrupt_cus_prod(self, prod, disrupted_up_prod):
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# parameter prod is the product that has disrupted_up_prod
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# parameter disrupted_up_prod is the product that
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# self's component exists disrupted supplier
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num_lost = \
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len(self.dct_prod_up_prod_stat[prod]['s_stat']
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[disrupted_up_prod]['set_disrupt_firm'])
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num_remain = \
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len([u for u, _, _, d in
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self.firm_network.in_edges(self.get_firm_network_unique_id(),
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keys=True,
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data='Product')
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if d == disrupted_up_prod.unique_id])
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lost_percent = num_lost / (num_lost + num_remain)
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lst_size = \
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[firm.size_stat[-1][0] for firm in self.model.company_agents]
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std_size = (self.size_stat[-1][0] - min(lst_size) + 1) \
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/ (max(lst_size) - min(lst_size) + 1)
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# calculate probability of disruption
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prob_disrupt = 1 - std_size * (1 - lost_percent)
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if self.model.nprandom.choice([True, False],
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p=[prob_disrupt,
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1 - prob_disrupt]):
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self.dct_n_trial_up_prod_disrupted[disrupted_up_prod] = 0
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self.dct_prod_up_prod_stat[
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prod]['s_stat'][disrupted_up_prod]['stat'] = False
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status, _ = self.dct_prod_up_prod_stat[
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prod]['p_stat'][-1]
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if status != 'D':
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self.dct_prod_up_prod_stat[
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prod]['p_stat'].append(('D', self.model.t))
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# print(f"{self.name}'s {prod.code} turn to D status due to "
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# f"disrupted supplier of {disrupted_up_prod.code}")
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def seek_alt_supply(self, product):
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if self.dct_n_trial_up_prod_disrupted[product] <= self.model.int_n_max_trial:
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if self.dct_n_trial_up_prod_disrupted[product] == 0:
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self.dct_cand_alt_supp_up_prod_disrupted[product] = [
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firm for firm in self.model.company_agents
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if firm.is_prod_in_current_normal(product)]
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if self.dct_cand_alt_supp_up_prod_disrupted[product]:
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lst_firm_connect = []
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if self.is_prf_conn:
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for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]:
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if self.firm_network.has_edge(self.unique_id, firm.unique_id) or \
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self.firm_network.has_edge(firm.unique_id, self.unique_id):
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lst_firm_connect.append(firm)
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if len(lst_firm_connect) == 0:
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if self.is_prf_size:
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lst_size = [firm.size_stat[-1][0] for firm in self.dct_cand_alt_supp_up_prod_disrupted[product]]
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lst_prob = [size / sum(lst_size) for size in lst_size]
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select_alt_supply = \
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self.random.choices(self.dct_cand_alt_supp_up_prod_disrupted[product], weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(self.dct_cand_alt_supp_up_prod_disrupted[product])
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elif len(lst_firm_connect) > 0:
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if self.is_prf_size:
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lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_connect]
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lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
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select_alt_supply = self.random.choices(lst_firm_connect, weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(lst_firm_connect)
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assert select_alt_supply.is_prod_in_current_normal(product)
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if product in select_alt_supply.dct_request_prod_from_firm:
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select_alt_supply.dct_request_prod_from_firm[product].append(self)
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else:
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select_alt_supply.dct_request_prod_from_firm[product] = [self]
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self.dct_n_trial_up_prod_disrupted[product] += 1
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def handle_request(self):
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for product, lst_firm in self.dct_request_prod_from_firm.items():
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if self.dct_prod_capacity[product] > 0:
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if len(lst_firm) == 0:
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continue
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elif len(lst_firm) == 1:
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self.accept_request(lst_firm[0], product)
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elif len(lst_firm) > 1:
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lst_firm_connect = []
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if self.is_prf_conn:
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for firm in lst_firm:
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if self.firm_network.has_edge(self.unique_id, firm.unique_id) or \
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self.firm_network.has_edge(firm.unique_id, self.unique_id):
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lst_firm_connect.append(firm)
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if len(lst_firm_connect) == 0:
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if self.is_prf_size:
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lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm]
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lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
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select_customer = self.random.choices(lst_firm, weights=lst_prob)[0]
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else:
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select_customer = self.random.choice(lst_firm)
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self.accept_request(select_customer, product)
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elif len(lst_firm_connect) > 0:
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if self.is_prf_size:
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lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_connect]
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lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
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select_customer = self.random.choices(lst_firm_connect, weights=lst_prob)[0]
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else:
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select_customer = self.random.choice(lst_firm_connect)
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self.accept_request(select_customer, product)
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else:
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for down_firm in lst_firm:
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down_firm.dct_cand_alt_supp_up_prod_disrupted[product].remove(self)
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def accept_request(self, down_firm, product):
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if self.firm_network.has_edge(self.unique_id, down_firm.unique_id) or \
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self.firm_network.has_edge(down_firm.unique_id, self.unique_id):
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prod_accept = 1.0
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else:
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prod_accept = self.flt_diff_new_conn
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if self.model.nprandom.choice([True, False], p=[prod_accept, 1 - prod_accept]):
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self.firm_network.add_edge(self.unique_id, down_firm.unique_id, Product=product.unique_id)
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self.dct_prod_capacity[product] -= 1
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self.dct_request_prod_from_firm[product].remove(down_firm)
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for prod in down_firm.dct_prod_up_prod_stat.keys():
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if product in down_firm.dct_prod_up_prod_stat[prod]['s_stat']:
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down_firm.dct_prod_up_prod_stat[prod]['s_stat'][product]['stat'] = True
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down_firm.dct_prod_up_prod_stat[prod]['p_stat'].append(
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('N', self.model.t))
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del down_firm.dct_n_trial_up_prod_disrupted[product]
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del down_firm.dct_cand_alt_supp_up_prod_disrupted[product]
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else:
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down_firm.dct_cand_alt_supp_up_prod_disrupted[product].remove(self)
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def seek_material_supply(self, material_type):
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lst_firm_material_connect = [] # 符合条件 可选择的上游
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upper_i_material = [] # 特定 资源的上游 企业集合
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for firm in self.upper_i:
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for sub_list in firm.R:
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if sub_list[0] == material_type:
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upper_i_material.append(firm)
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# 没有 上游 没有 材料的情况，也就是紊乱的情况
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# if len(upper_i_material)==0:
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if self.is_prf_conn:
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for firm in upper_i_material:
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if self.firm_network.has_edge(self.unique_id, firm.unique_id) or self.firm_network.has_edge(
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firm.unique_id, self.unique_id):
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lst_firm_material_connect.append(firm)
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if len(lst_firm_material_connect) == 0:
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if self.is_prf_size:
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lst_size = [firm.size_stat[-1][0] for firm in upper_i_material]
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lst_prob = [size / sum(lst_size) for size in lst_size]
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select_alt_supply = \
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self.random.choices(upper_i_material, weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(upper_i_material)
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elif len(lst_firm_material_connect) > 0:
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if self.is_prf_size:
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lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_material_connect]
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lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
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select_alt_supply = self.random.choices(lst_firm_material_connect, weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(lst_firm_material_connect)
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return select_alt_supply
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def seek_machinery_supply(self, machinery_type):
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lst_firm_machinery_connect = [] # 符合条件 可选择的上游
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upper_i_machinery = [] # 特定 资源的上游 企业集合
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for firm in self.upper_i:
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for sub_list in firm.R:
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if sub_list[0] == machinery_type:
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upper_i_machinery.append(firm)
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# 没有 上游 没有 材料的情况，也就是紊乱的情况
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# if len(upper_i_machinery)==0:
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if self.is_prf_conn:
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for firm in upper_i_machinery:
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if self.firm_network.has_edge(self.unique_id, firm.unique_id) or self.firm_network.has_edge(
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firm.unique_id, self.unique_id):
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lst_firm_machinery_connect.append(firm)
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if len(lst_firm_machinery_connect) == 0:
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if self.is_prf_size:
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lst_size = [firm.size_stat[-1][0] for firm in upper_i_machinery]
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lst_prob = [size / sum(lst_size) for size in lst_size]
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select_alt_supply = \
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self.random.choices(upper_i_machinery, weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(upper_i_machinery)
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elif len(lst_firm_machinery_connect) > 0:
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if self.is_prf_size:
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lst_firm_size = [firm.size_stat[-1][0] for firm in lst_firm_machinery_connect]
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lst_prob = [size / sum(lst_firm_size) for size in lst_firm_size]
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select_alt_supply = self.random.choices(lst_firm_machinery_connect, weights=lst_prob)[0]
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else:
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select_alt_supply = self.random.choice(lst_firm_machinery_connect)
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return select_alt_supply
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def handle_material_request(self, material_list):
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for list in self.P:
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if list[0] == material_list[0]:
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list[1] -= material_list[1]
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def handle_machinery_request(self, machinery_list):
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for list in self.C:
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if list[0] == machinery_list[0]:
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list[1] -= machinery_list[1]
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def refresh_R(self):
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self.R1[self.model.t] = self.R
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def refresh_C(self):
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self.C1[self.model.t] = self.C
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def refresh_P(self):
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self.P1[self.model.t] = self.P
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def clean_before_trial(self):
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self.dct_request_prod_from_firm = {}
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def clean_before_time_step(self):
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# Reset the number of trials and candidate suppliers for disrupted products
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self.dct_n_trial_up_prod_disrupted = dict.fromkeys(self.dct_n_trial_up_prod_disrupted.keys(), 0)
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self.dct_cand_alt_supp_up_prod_disrupted = {}
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# Update the status of products and refresh disruption sets
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for prod in self.dct_prod_up_prod_stat.keys():
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status, ts = self.dct_prod_up_prod_stat[prod]['p_stat'][-1]
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if ts != self.model.t:
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self.dct_prod_up_prod_stat[prod]['p_stat'].append((status, self.model.t))
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# Refresh the set of disrupted firms
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for up_prod in self.dct_prod_up_prod_stat[prod]['s_stat'].keys():
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self.dct_prod_up_prod_stat[prod]['s_stat'][up_prod]['set_disrupt_firm'] = set()
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def get_firm_network_unique_id(self):
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return self.unique_id
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def is_prod_in_current_normal(self, prod):
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if prod in self.dct_prod_up_prod_stat.keys():
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if self.dct_prod_up_prod_stat[prod]['p_stat'][-1][0] == 'N':
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return True
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else:
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return False
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else:
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return False
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