remove crit_supplier
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@ -117,7 +117,7 @@ class ControllerDB:
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dct_lst_init_disrupt_firm_prod, g_bom,
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n_max_trial, prf_size, prf_conn,
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cap_limit_prob_type, cap_limit_level,
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diff_new_conn, crit_supplier,
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diff_new_conn,
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proactive_ratio, remove_t, netw_prf_n):
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e = Experiment(
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idx_scenario=idx_scenario,
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@ -132,7 +132,6 @@ class ControllerDB:
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cap_limit_prob_type=cap_limit_prob_type,
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cap_limit_level=cap_limit_level,
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diff_new_conn=diff_new_conn,
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crit_supplier=crit_supplier,
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proactive_ratio=proactive_ratio,
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remove_t=remove_t,
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netw_prf_n=netw_prf_n
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96
firm.py
96
firm.py
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@ -1,5 +1,4 @@
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import agentpy as ap
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import math
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class FirmAgent(ap.Agent):
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@ -26,7 +25,6 @@ class FirmAgent(ap.Agent):
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self.str_cap_limit_prob_type = str(self.p.cap_limit_prob_type)
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self.flt_cap_limit_level = float(self.p.cap_limit_level)
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self.flt_diff_new_conn = float(self.p.diff_new_conn)
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self.flt_crit_supplier = float(self.p.crit_supplier)
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# init size_stat (self para)
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# (size, time step)
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@ -36,9 +34,14 @@ class FirmAgent(ap.Agent):
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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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# (Normal / Disrupted / Removed, time step)
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'status': [('N', 0)],
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'p_stat': [('N', 0)],
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# have or have no supply
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'supply': dict.fromkeys(prod.a_predecessors(), True)
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'supply': dict.fromkeys(prod.a_predecessors(), True),
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# supply for each component and respective disrupted supplier
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# lst_disrupt_firm is refreshed to [] at each update
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's_stat': dict.fromkeys(prod.a_predecessors(),
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{'stat': True,
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'lst_disrupt_firm': []})
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}
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# init extra capacity (self para)
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@ -62,45 +65,58 @@ class FirmAgent(ap.Agent):
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# print(firm_agent.name, extra_cap)
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self.dct_prod_capacity[product] = extra_cap
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def remove_edge_to_cus_disrupt_cus_up_prod(self, disrupted_prod):
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def remove_edge_to_cus(self, disrupted_prod):
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# para disrupted_prod is the product that self got disrupted
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lst_out_edge = list(
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self.firm_network.graph.out_edges(
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self.firm_network.positions[self], 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.code:
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# update customer up product supplier status
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customer = ap.AgentIter(self.model, n2).to_list()[0]
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for prod in customer.dct_prod_up_prod_stat.keys():
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if disrupted_prod in \
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customer.dct_prod_up_prod_stat[
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prod]['s_stat'].keys():
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if self not in customer.dct_prod_up_prod_stat[
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prod]['s_stat'][disrupted_prod][
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'lst_disrupt_firm']:
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customer.dct_prod_up_prod_stat[
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prod]['s_stat'][disrupted_prod][
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'lst_disrupt_firm'].append(self)
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# remove edge to customer
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self.firm_network.graph.remove_edge(n1, n2, key)
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# customer up product affected conditionally
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customer = ap.AgentIter(self.model, n2).to_list()[0]
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lst_in_edge = list(
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self.firm_network.graph.in_edges(n2,
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keys=True,
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data='Product'))
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lst_select_in_edge = [
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edge for edge in lst_in_edge
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if edge[-1] == disrupted_prod.code
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]
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prob_lost_supp = math.exp(-1 * self.flt_crit_supplier *
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len(lst_select_in_edge))
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if self.model.nprandom.choice([True, False],
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p=[prob_lost_supp,
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1 - prob_lost_supp]):
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customer.dct_n_trial_up_prod_disrupted[disrupted_prod] = 0
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for prod in customer.dct_prod_up_prod_stat.keys():
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if disrupted_prod in \
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customer.dct_prod_up_prod_stat[
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prod]['supply'].keys():
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customer.dct_prod_up_prod_stat[
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prod]['supply'][disrupted_prod] = False
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status, _ = customer.dct_prod_up_prod_stat[
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prod]['status'][-1]
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if status != 'D':
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customer.dct_prod_up_prod_stat[
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prod]['status'].append(('D', self.model.t))
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# print(self.name, disrupted_prod.code, 'disrupt',
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# customer.name, prod.code)
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def disrupt_cus_prod(self, prod, disrupted_up_prod):
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# para prod is the product that has disrupted_up_prod
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# para 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]['lst_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.graph.in_edges(self.get_firm_network_node(),
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keys=True,
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data='Product')
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if d == disrupted_up_prod.code])
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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.a_lst_total_firms]
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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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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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def seek_alt_supply(self, product):
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# para product is the product that self is seeking
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@ -270,7 +286,7 @@ class FirmAgent(ap.Agent):
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down_firm.dct_prod_up_prod_stat[
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prod]['supply'][product] = True
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down_firm.dct_prod_up_prod_stat[
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prod]['status'].append(('N', self.model.t))
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prod]['p_stat'].append(('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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@ -296,17 +312,21 @@ class FirmAgent(ap.Agent):
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# update the status of firm
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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]['status'][-1]
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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]['status'].append(
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self.dct_prod_up_prod_stat[prod]['p_stat'].append(
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(status, self.model.t))
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# refresh lst_disrupt_firm
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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][
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's_stat'][up_prod]['lst_disrupt_firm'] = []
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def get_firm_network_node(self):
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return self.firm_network.positions[self]
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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]['status'][-1][0] == 'N':
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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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30
model.py
30
model.py
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@ -228,7 +228,7 @@ class Model(ap.Model):
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assert product in firm.dct_prod_up_prod_stat.keys(), \
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f"product {product.code} not in firm {firm.code}"
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firm.dct_prod_up_prod_stat[
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product]['status'].append(('D', self.t))
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product]['p_stat'].append(('D', self.t))
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# print(f"initial disruption {firm.name} {product.code}")
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# proactive strategy
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@ -349,7 +349,7 @@ class Model(ap.Model):
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# reduce the size of disrupted firm
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for firm in self.a_lst_total_firms:
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for prod in firm.dct_prod_up_prod_stat.keys():
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status, ts = firm.dct_prod_up_prod_stat[prod]['status'][-1]
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status, ts = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
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if status == 'D':
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size = firm.size_stat[-1][0] - \
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firm.size_stat[0][0] \
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@ -360,19 +360,19 @@ class Model(ap.Model):
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# f'to {firm.size_stat[-1][0]} due to {prod.code}')
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lst_is_disrupt = \
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[stat == 'D' for stat, _ in
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firm.dct_prod_up_prod_stat[prod]['status']
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firm.dct_prod_up_prod_stat[prod]['p_stat']
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[-1 * self.remove_t:]]
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if all(lst_is_disrupt):
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# turn disrupted firm into removed firm
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# when last self.remove_t times status is all disrupted
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firm.dct_prod_up_prod_stat[
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prod]['status'].append(('R', self.t))
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prod]['p_stat'].append(('R', self.t))
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# stop simulation if any firm still in disrupted except inital removal
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if self.t > 0:
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for firm in self.a_lst_total_firms:
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for prod in firm.dct_prod_up_prod_stat.keys():
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status, _ = firm.dct_prod_up_prod_stat[prod]['status'][-1]
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status, _ = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
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is_init = \
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firm in self.dct_lst_init_disrupt_firm_prod.keys() \
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and prod in self.dct_lst_init_disrupt_firm_prod[firm]
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@ -397,9 +397,17 @@ class Model(ap.Model):
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for prod in firm.dct_prod_up_prod_stat.keys():
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# repetition of disrupted firm that last for multiple ts is ok,
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# as their edge has already been removed
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status, ts = firm.dct_prod_up_prod_stat[prod]['status'][-1]
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status, ts = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1]
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if status == 'D' and ts == self.t-1:
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firm.remove_edge_to_cus_disrupt_cus_up_prod(prod)
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firm.remove_edge_to_cus(prod)
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for firm in self.a_lst_total_firms:
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for prod in firm.dct_prod_up_prod_stat.keys():
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for up_prod in firm.dct_prod_up_prod_stat[prod][
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's_stat'].keys():
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if firm.dct_prod_up_prod_stat[prod][
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's_stat'][up_prod]['lst_disrupt_firm']:
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firm.disrupt_cus_prod(prod, up_prod)
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for n_trial in range(self.int_n_max_trial):
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# print('=' * 10, 'trial', n_trial, '=' * 10)
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@ -410,7 +418,7 @@ class Model(ap.Model):
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for firm in self.a_lst_total_firms:
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lst_seek_prod = []
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for prod in firm.dct_prod_up_prod_stat.keys():
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status = firm.dct_prod_up_prod_stat[prod]['status'][-1][0]
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status = firm.dct_prod_up_prod_stat[prod]['p_stat'][-1][0]
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if status == 'D':
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for supply in firm.dct_prod_up_prod_stat[
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prod]['supply'].keys():
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@ -448,11 +456,11 @@ class Model(ap.Model):
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for prod, dct_status_supply in \
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firm.dct_prod_up_prod_stat.items():
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lst_is_normal = [stat == 'N' for stat, _
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in dct_status_supply['status']]
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in dct_status_supply['p_stat']]
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if not all(lst_is_normal):
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# print(f"{firm.name} {prod.code}:")
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# print(dct_status_supply['status'])
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for status, ts in dct_status_supply['status']:
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# print(dct_status_supply['p_stat'])
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for status, ts in dct_status_supply['p_stat']:
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db_r = Result(s_id=self.sample.id,
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id_firm=firm.code,
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id_product=prod.code,
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@ -1,37 +1,37 @@
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X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18,X19,X20,X21,X22,X23
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0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
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1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1
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2,0,0,0,2,2,2,2,2,2,0,0,0,0,0,0,0,0,2,2,2,2,2
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0,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,2,2,2,2
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1,0,0,0,1,1,1,2,2,2,0,0,1,1,1,1,1,1,2,0,0,0,0
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2,0,0,0,2,2,2,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1
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0,0,0,1,0,1,2,0,1,2,1,1,0,0,0,1,1,1,2,0,1,1,2
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1,0,0,1,1,2,0,1,2,0,1,1,0,0,0,1,1,1,0,1,2,2,0
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2,0,0,1,2,0,1,2,0,1,1,1,0,0,0,1,1,1,1,2,0,0,1
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0,0,1,0,0,2,1,0,2,1,1,1,0,1,1,0,0,1,2,1,0,2,1
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1,0,1,0,1,0,2,1,0,2,1,1,0,1,1,0,0,1,0,2,1,0,2
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2,0,1,0,2,1,0,2,1,0,1,1,0,1,1,0,0,1,1,0,2,1,0
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0,0,1,1,1,2,0,2,1,0,0,1,1,0,1,0,1,0,2,2,1,0,1
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1,0,1,1,2,0,1,0,2,1,0,1,1,0,1,0,1,0,0,0,2,1,2
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2,0,1,1,0,1,2,1,0,2,0,1,1,0,1,0,1,0,1,1,0,2,0
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0,0,1,1,1,2,1,0,0,2,1,0,1,1,0,1,0,0,1,2,2,1,0
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1,0,1,1,2,0,2,1,1,0,1,0,1,1,0,1,0,0,2,0,0,2,1
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2,0,1,1,0,1,0,2,2,1,1,0,1,1,0,1,0,0,0,1,1,0,2
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0,1,0,1,1,0,2,2,2,0,1,0,0,1,1,0,1,0,1,1,0,1,2
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1,1,0,1,2,1,0,0,0,1,1,0,0,1,1,0,1,0,2,2,1,2,0
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2,1,0,1,0,2,1,1,1,2,1,0,0,1,1,0,1,0,0,0,2,0,1
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0,1,0,1,1,1,2,2,0,1,0,1,1,1,0,0,0,1,0,0,2,2,1
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1,1,0,1,2,2,0,0,1,2,0,1,1,1,0,0,0,1,1,1,0,0,2
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2,1,0,1,0,0,1,1,2,0,0,1,1,1,0,0,0,1,2,2,1,1,0
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0,1,0,0,2,1,0,1,2,2,1,1,1,0,1,1,0,0,0,2,0,1,1
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1,1,0,0,0,2,1,2,0,0,1,1,1,0,1,1,0,0,1,0,1,2,2
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||||
2,1,0,0,1,0,2,0,1,1,1,1,1,0,1,1,0,0,2,1,2,0,0
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||||
0,1,1,1,2,1,1,1,0,0,0,0,0,0,1,1,0,1,2,1,2,0,2
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1,1,1,1,0,2,2,2,1,1,0,0,0,0,1,1,0,1,0,2,0,1,0
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2,1,1,1,1,0,0,0,2,2,0,0,0,0,1,1,0,1,1,0,1,2,1
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0,1,1,0,2,2,2,1,2,1,1,0,1,0,0,0,1,1,1,0,1,0,0
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1,1,1,0,0,0,0,2,0,2,1,0,1,0,0,0,1,1,2,1,2,1,1
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2,1,1,0,1,1,1,0,1,0,1,0,1,0,0,0,1,1,0,2,0,2,2
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0,1,1,0,2,0,1,2,1,2,0,1,0,1,0,1,1,0,0,1,1,2,0
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1,1,1,0,0,1,2,0,2,0,0,1,0,1,0,1,1,0,1,2,2,0,1
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2,1,1,0,1,2,0,1,0,1,0,1,0,1,0,1,1,0,2,0,0,1,2
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1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1
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2,0,0,0,2,2,2,2,2,0,0,0,0,0,0,0,0,2,2,2,2,2,2
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0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,2,2,2,2
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1,0,0,0,1,1,1,2,2,0,0,1,1,1,1,1,1,2,2,0,0,0,0
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2,0,0,0,2,2,2,0,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1
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0,0,0,1,0,1,2,0,1,1,1,0,0,0,1,1,1,2,2,0,1,1,2
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1,0,0,1,1,2,0,1,2,1,1,0,0,0,1,1,1,0,0,1,2,2,0
|
||||
2,0,0,1,2,0,1,2,0,1,1,0,0,0,1,1,1,1,1,2,0,0,1
|
||||
0,0,1,0,0,2,1,0,2,1,1,0,1,1,0,0,1,1,2,1,0,2,1
|
||||
1,0,1,0,1,0,2,1,0,1,1,0,1,1,0,0,1,2,0,2,1,0,2
|
||||
2,0,1,0,2,1,0,2,1,1,1,0,1,1,0,0,1,0,1,0,2,1,0
|
||||
0,0,1,1,1,2,0,2,1,0,1,1,0,1,0,1,0,0,2,2,1,0,1
|
||||
1,0,1,1,2,0,1,0,2,0,1,1,0,1,0,1,0,1,0,0,2,1,2
|
||||
2,0,1,1,0,1,2,1,0,0,1,1,0,1,0,1,0,2,1,1,0,2,0
|
||||
0,0,1,1,1,2,1,0,0,1,0,1,1,0,1,0,0,2,1,2,2,1,0
|
||||
1,0,1,1,2,0,2,1,1,1,0,1,1,0,1,0,0,0,2,0,0,2,1
|
||||
2,0,1,1,0,1,0,2,2,1,0,1,1,0,1,0,0,1,0,1,1,0,2
|
||||
0,1,0,1,1,0,2,2,2,1,0,0,1,1,0,1,0,0,1,1,0,1,2
|
||||
1,1,0,1,2,1,0,0,0,1,0,0,1,1,0,1,0,1,2,2,1,2,0
|
||||
2,1,0,1,0,2,1,1,1,1,0,0,1,1,0,1,0,2,0,0,2,0,1
|
||||
0,1,0,1,1,1,2,2,0,0,1,1,1,0,0,0,1,1,0,0,2,2,1
|
||||
1,1,0,1,2,2,0,0,1,0,1,1,1,0,0,0,1,2,1,1,0,0,2
|
||||
2,1,0,1,0,0,1,1,2,0,1,1,1,0,0,0,1,0,2,2,1,1,0
|
||||
0,1,0,0,2,1,0,1,2,1,1,1,0,1,1,0,0,2,0,2,0,1,1
|
||||
1,1,0,0,0,2,1,2,0,1,1,1,0,1,1,0,0,0,1,0,1,2,2
|
||||
2,1,0,0,1,0,2,0,1,1,1,1,0,1,1,0,0,1,2,1,2,0,0
|
||||
0,1,1,1,2,1,1,1,0,0,0,0,0,1,1,0,1,0,2,1,2,0,2
|
||||
1,1,1,1,0,2,2,2,1,0,0,0,0,1,1,0,1,1,0,2,0,1,0
|
||||
2,1,1,1,1,0,0,0,2,0,0,0,0,1,1,0,1,2,1,0,1,2,1
|
||||
0,1,1,0,2,2,2,1,2,1,0,1,0,0,0,1,1,1,1,0,1,0,0
|
||||
1,1,1,0,0,0,0,2,0,1,0,1,0,0,0,1,1,2,2,1,2,1,1
|
||||
2,1,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,0,0,2,0,2,2
|
||||
0,1,1,0,2,0,1,2,1,0,1,0,1,0,1,1,0,2,0,1,1,2,0
|
||||
1,1,1,0,0,1,2,0,2,0,1,0,1,0,1,1,0,0,1,2,2,0,1
|
||||
2,1,1,0,1,2,0,1,0,0,1,0,1,0,1,1,0,1,2,0,0,1,2
|
||||
|
|
|
BIN
oa_with_exp.xlsx
BIN
oa_with_exp.xlsx
Binary file not shown.
|
@ -1,2 +1,2 @@
|
|||
X1,X2,X3,X4,X5,X6,X7,X8,X9,X10
|
||||
0,0,0,0,0,0,0,0,0,0
|
||||
X1,X2,X3,X4,X5,X6,X7,X8,X9
|
||||
0,0,0,0,0,0,0,0,0
|
||||
|
|
|
1
orm.py
1
orm.py
|
@ -60,7 +60,6 @@ class Experiment(Base):
|
|||
cap_limit_prob_type = Column(String(16), nullable=False)
|
||||
cap_limit_level = Column(DECIMAL(8, 4), nullable=False)
|
||||
diff_new_conn = Column(DECIMAL(8, 4), nullable=False)
|
||||
crit_supplier = Column(DECIMAL(8, 4), nullable=False)
|
||||
proactive_ratio = Column(DECIMAL(8, 4), nullable=False)
|
||||
remove_t = Column(Integer, nullable=False)
|
||||
netw_prf_n = Column(Integer, nullable=False)
|
||||
|
|
|
@ -1,4 +1,4 @@
|
|||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,proactive_ratio,remove_t,netw_prf_n
|
||||
7,TRUE,TRUE,uniform,5,0.3,2,0.3,3,3
|
||||
5,FALSE,FALSE,normal,10,0.5,1,0.5,5,2
|
||||
3,,,,15,0.7,0.5,0.7,7,1
|
||||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,proactive_ratio,remove_t,netw_prf_n
|
||||
7,TRUE,TRUE,uniform,5,0.3,0.3,3,3
|
||||
5,FALSE,FALSE,normal,10,0.5,0.5,5,2
|
||||
3,,,,15,0.7,0.7,7,1
|
||||
|
|
|
|
@ -1,2 +1,2 @@
|
|||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,proactive_ratio,remove_t,netw_prf_n
|
||||
5,TRUE,TRUE,uniform,10,0.5,1,0,5,2
|
||||
n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,proactive_ratio,remove_t,netw_prf_n
|
||||
5,TRUE,TRUE,uniform,10,0.5,0,5,2
|
||||
|
|
|
Loading…
Reference in New Issue