capacity init network
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21
firm.py
21
firm.py
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@ -29,12 +29,23 @@ class FirmAgent(ap.Agent):
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# remove edge
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# print(n1, n2, key, product_code)
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self.firm_network.graph.remove_edge(n1, n2, key)
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# remove customer up product
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# remove customer up product if does not have alternative
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customer = ap.AgentIter(self.model, n2).to_list()[0]
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if remove_product not in customer.a_list_up_product_removed:
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customer.a_list_up_product_removed.append(remove_product)
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customer.dct_num_trial_up_product_removed[
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remove_product] = 0
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list_in_edges = 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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select_edges = [
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edge for edge in list_in_edges
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if edge[-1] == remove_product.code
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]
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if len(select_edges) == 0:
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if remove_product not in \
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customer.a_list_up_product_removed:
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customer.a_list_up_product_removed.append(
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remove_product)
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customer.dct_num_trial_up_product_removed[
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remove_product] = 0
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# # disrupt customer
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# customer = ap.AgentIter(self.model, n2).to_list()[0]
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54
model.py
54
model.py
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@ -71,20 +71,29 @@ class Model(ap.Model):
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G_Firm.nodes[succ_firm]['Revenue_Log']
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for succ_firm in list_succ_firms
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]
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# list_prob = [
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# (v - min(list_revenue_log) + 1) /
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# (max(list_revenue_log) - min(list_revenue_log) + 1)
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# for v in list_revenue_log
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# ]
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# list_flag = [
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# self.nprandom.choice([1, 0], p=[prob, 1 - prob])
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# for prob in list_prob
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# ]
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# # print(list(zip(list_succ_firms,list_flag,list_prob)))
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# list_added_edges = [(node, succ_firm, {
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# 'Product': product_code
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# }) for succ_firm, flag in zip(list_succ_firms, list_flag)
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# if flag == 1]
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list_prob = [
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(v - min(list_revenue_log) + 1) /
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(max(list_revenue_log) - min(list_revenue_log) + 1)
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for v in list_revenue_log
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size / sum(list_revenue_log)
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for size in list_revenue_log
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]
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list_flag = [
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self.nprandom.choice([1, 0], p=[prob, 1 - prob])
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for prob in list_prob
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]
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# print(list(zip(list_succ_firms,list_flag,list_prob)))
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succ_firm = self.nprandom.choice(list_succ_firms,
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p=list_prob)
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list_added_edges = [(node, succ_firm, {
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'Product': product_code
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}) for succ_firm, flag in zip(list_succ_firms, list_flag)
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if flag == 1]
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})]
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G_Firm.add_edges_from(list_added_edges)
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# print('-' * 20)
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@ -118,16 +127,19 @@ class Model(ap.Model):
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code in attr['Product_Code']
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for code in self.a_list_total_products.code
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]))
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# init capacity as the degree of out edges of a specific product
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list_out_edges = list(
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self.firm_network.graph.out_edges(ag_node,
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keys=True,
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data='Product'))
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# init capacity based on discrete uniform distribution
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# list_out_edges = list(
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# self.firm_network.graph.out_edges(ag_node,
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# keys=True,
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# data='Product'))
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# for product in firm_agent.a_list_product:
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# capacity = len([
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# edge for edge in list_out_edges if edge[-1] ==
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# product.code])
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# firm_agent.dct_prod_capacity[product] = capacity
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for product in firm_agent.a_list_product:
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capacity = len([
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edge for edge in list_out_edges if edge[-1] == product.code
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])
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firm_agent.dct_prod_capacity[product] = capacity
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firm_agent.dct_prod_capacity[product] = self.nprandom.integers(
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firm_agent.revenue_log / 5, firm_agent.revenue_log / 5 + 2)
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# print(firm_agent.name, firm_agent.dct_prod_capacity)
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self.firm_network.add_agents([firm_agent], [ag_node])
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@ -184,7 +196,7 @@ class Model(ap.Model):
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firm.remove_edge_to_cus_and_cus_up_prod(product)
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for n_trial in range(self.int_n_max_trial):
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print('='*20, n_trial, '='*20)
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print('=' * 20, n_trial, '=' * 20)
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# seek_alt_supply
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for firm in self.a_list_total_firms:
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if len(firm.a_list_up_product_removed) > 0:
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@ -241,6 +253,6 @@ class Model(ap.Model):
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model = Model(dct_sample_para)
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model.setup()
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model.draw_network()
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model.update()
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model.step()
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# model.draw_network()
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BIN
network.png
BIN
network.png
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22
test.ipynb
22
test.ipynb
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@ -1,5 +1,27 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import numpy as np\n",
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"\n",
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"np.random.randint(0.5, 3.5)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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