优化 干扰列表
This commit is contained in:
Cricial
parent
13521ff752
commit
3a46d09b8e
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@ -3,6 +3,13 @@
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<component name="CsvFileAttributes">
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<option name="attributeMap">
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<map>
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<entry key="C:\Users\www\Desktop\python项目\数据\抽样第3次数据\firm_amended.csv">
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<value>
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<Attribute>
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<option name="separator" value="," />
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</Attribute>
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</value>
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</entry>
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<entry key="\input_data\device_salvage_values.csv">
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<value>
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<Attribute>
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@ -67,12 +67,27 @@ class ControllerDB:
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# 行索引 (index)：这一行在数据帧中的索引值。
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# 行数据 (row)：这一行的数据，是一个 pandas.Series 对象，包含该行的所有列和值。
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# 读取企业与产品关系数据
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firm_industry = pd.read_csv("input_data/firm_industry_relation.csv")
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firm_industry['Firm_Code'] = firm_industry['Firm_Code'].astype('string')
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# 假设已从 BOM 数据构建了 code_to_indices
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bom_nodes = pd.read_csv("input_data/input_product_data/BomNodes.csv")
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code_to_indices = bom_nodes.groupby('Code')['Index'].apply(list).to_dict()
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# 初始化存储映射结果的列表
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list_dct = []
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# 遍历 firm_industry 数据
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for _, row in firm_industry.iterrows():
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code = row['Firm_Code']
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row = row['Product_Code']
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dct = {code: [row]}
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firm_code = row['Firm_Code'] # 企业代码
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product_code = row['Product_Code'] # 原始产品代码
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# 使用 code_to_indices 映射 Product_Code 到 Product_Indices
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mapped_indices = code_to_indices.get(product_code, []) # 如果找不到则返回空列表
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# 构建企业到产品索引的映射
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dct = {firm_code: mapped_indices}
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list_dct.append(dct)
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# fill g_bom
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10
firm.py
10
firm.py
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@ -32,13 +32,13 @@ class FirmAgent(Agent):
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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 = [agent for u, v in self.firm_network.in_edges(self.unique_id)
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for agent in self.model.company_agents if agent.unique_id == u]
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self.upper_i = [self.model.agent_map[u] for u, v in self.firm_network.in_edges(self.unique_id)
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if u in self.model.agent_map]
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# 企业i的客户
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self.downer_i = [agent for u, v in self.firm_network.out_edges(self.unique_id)
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for agent in self.model.company_agents if agent.unique_id == u]
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self.downer_i = [self.model.agent_map[v] for u, v in self.firm_network.out_edges(self.unique_id)
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if v in self.model.agent_map]
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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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# self.n_equip_c = n_equip_c
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# 设备c产量 根据设备量进行估算
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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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@ -220,3 +220,22 @@
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11164476478,20163.0918395453,11651.4309309683,28954.8221299891,1830.10798,江苏芯诺半导体科技有限公司,江苏省,4.5,0
|
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11212932825,491.782727793788,284.181242218739,706.215173902172,44.63678,河南雷电光源技术研究院,河南省,2.8,0
|
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11220388001,737.674091690682,426.271863328108,1059.32276085326,66.95517,新疆蚂蚁网约出租汽车服务有限公司,新疆维吾尔自治区,3.0,0
|
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397847929,4794.881596,2770.767112,6885.597946,435.208605,厦门科塔电子有限公司,福建省,3.8,0
|
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517717050,40080.29232,23160.77124,57556.53667,3637.89757,深圳市实锐泰科技有限公司,广东省,4.8,0
|
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737770776,5962.865574,3445.697562,8562.858984,541.2209575,福建省南安市物资有限公司,福建省,3.9,0
|
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872394725,25724.57103,15462.17311,55978.44597,7283.825438,北京凯德石英股份有限公司,北京市,4.7,0
|
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2311581270,32088.82299,18542.82605,46080.5401,2912.549895,安徽亚格盛电子新材料股份有限公司,安徽省,4.7,0
|
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2313209417,15122.31888,8738.573198,21716.1166,1372.580985,武汉拓材科技有限公司,湖北省,4.3,0
|
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2347013470,23006.64933,17588.56669,81317.91108,12851.94016,江苏先锋精密科技股份有限公司,江苏省,4.9,0
|
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2350418059,73931.33674,42721.91341,106167.6811,6710.395927,江苏纳沛斯半导体有限公司,江苏省,5.0,0
|
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2352951203,29261.0723,16908.78391,42019.80285,2655.88841,中山市江波龙电子有限公司,广东省,4.6,0
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2359644835,232613.2302,134417.7276,334039.7773,21113.19694,广东气派科技有限公司,广东省,5.5,0
|
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2388955897,2458.913639,1420.906211,3531.07587,223.1839,上海鑫匀源科技有限公司,上海市,3.5,0
|
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2977767486,9790.429458,5657.491099,14059.35884,1748.344959,深圳市三联盛科技股份有限公司,广东省,4.1,0
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3031009366,43768.66277,25292.13056,62853.15048,3972.67342,天通瑞宏科技有限公司,浙江省,4.8,0
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3089095447,245.8913639,142.0906211,353.107587,22.31839,常州金坛沸腾商贸有限公司,江苏省,2.5,0
|
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3100891962,14801.53049,8553.202633,21255.45458,3889.830944,北京中超伟业信息安全技术股份有限公司,北京市,4.3,0
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3151203276,341884.6624,201430.569,477385.6924,28574.49401,合肥颀中科技股份有限公司,安徽省,5.7,0
|
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3188352290,13032.24229,7530.802919,18714.70211,1182.87467,湖北深紫科技有限公司,湖北省,4.3,0
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3288105727,6639.066825,3836.44677,9533.904848,602.59653,奥趋光电技术（杭州）有限公司,浙江省,4.0,0
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3462551351,5901.392734,3410.174907,8474.582087,535.64136,无锡博加电子新材料有限公司,江苏省,3.9,0
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216
my_model.py
216
my_model.py
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@ -42,6 +42,7 @@ class MyModel(Model):
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- seed (int): 随机种子的值，用于确保实验的可重复性。
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"""
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# 仿真参数
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self.agent_map = None
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self.firm_prod_labels_dict = None
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self.firm_relationship_cache = None
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self.firm_product_cache = None
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@ -85,12 +86,22 @@ class MyModel(Model):
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self.company_agents = [] # 初始化公司代理列表
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# 初始化模型的网络和代理
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# 检查缓存是否存在
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cache_file = "firm_network.pkl"
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if os.path.exists(cache_file):
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# 从缓存加载 firm_network
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with open(cache_file, 'rb') as f:
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self.firm_network = pickle.load(f)
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print("Loaded firm network from cache.")
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else:
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# 执行完整的初始化流程
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self.initialize_product_network(params)
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self.initialize_firm_network()
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self.build_firm_prod_labels_dict()
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self.initialize_firm_product_network()
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self.add_edges_to_firm_network()
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self.connect_unconnected_nodes()
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self.initialize_product_network(params) # 初始化产品网络。
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self.initialize_firm_network() # 初始化企业网络。
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self.build_firm_prod_labels_dict() # 构建企业与产品的映射关系字典
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self.initialize_firm_product_network() # 初始化企业与产品的网络。
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self.add_edges_to_firm_network() # 添加企业之间的边。
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self.connect_unconnected_nodes() # 连接未连接的节点。
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self.resource_integration()
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self.j_comp_consumed_produced()
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self.initialize_agents() # 初始化代理。
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@ -402,8 +413,12 @@ class MyModel(Model):
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if current_node != -1 and succ_node != -1:
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self.firm_prod_network.add_edge(current_node, succ_node)
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# 保存网络数据到样本
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self.firm_prod_network = self.firm_prod_network # 使用 networkx 图对象表示的企业与产品关系网络
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# 保存构建完成的 firm_network 到缓存
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cache_file = "firm_network.pkl"
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os.makedirs("cache", exist_ok=True)
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with open(cache_file, 'wb') as f:
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pickle.dump(self.firm_network, f)
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# print("Firm network has been saved to cache.")
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def initialize_agents(self):
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"""
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@ -442,7 +457,8 @@ class MyModel(Model):
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C = self.firm_resource_C.loc[int(ag_node)]
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except KeyError:
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R, P, C = [], {}, [] # 如果任何资源不存在，返回空列表
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# 在模型初始化时，构建 unique_id -> agent 的快速映射字典
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self.agent_map = {agent.unique_id: agent for agent in self.company_agents}
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# 创建企业代理
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firm_agent = FirmAgent(
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unique_id=ag_node,
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@ -466,14 +482,25 @@ class MyModel(Model):
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- 更新公司与产品的生产状态为干扰状态。
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"""
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# 构建公司与受干扰产品的映射字典
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disruption_mapping = {
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firm: [
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product for product in self.product_agents
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if product.unique_id in lst_product
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disruption_mapping = {}
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for firm_code, lst_product_indices in self.dct_lst_init_disrupt_firm_prod.items():
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# 查找企业对象
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firm = next((f for f in self.company_agents if f.unique_id == firm_code), None)
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if not firm:
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print(f"Warning: Firm {firm_code} not found. Skipping.")
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continue
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# 查找有效的产品代理
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valid_products = [
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product for product in self.product_agents if product.unique_id in lst_product_indices
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]
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for firm_code, lst_product in self.dct_lst_init_disrupt_firm_prod.items()
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if (firm := next((f for f in self.company_agents if f.unique_id == firm_code), None))
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}
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if not valid_products:
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print(f"Warning: No valid products found for Firm {firm_code}. Skipping.")
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continue
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# 更新映射
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disruption_mapping[firm] = valid_products
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# 更新干扰字典
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self.dct_lst_init_disrupt_firm_prod = disruption_mapping
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@ -481,10 +508,13 @@ class MyModel(Model):
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# 设置初始干扰状态
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for firm, disrupted_products in disruption_mapping.items():
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for product in disrupted_products:
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# 确保产品在公司的生产状态中
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# 检查产品是否在企业的生产状态中
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if product not in firm.dct_prod_up_prod_stat:
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raise ValueError(
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f"Product {product.unique_id} not found in firm {firm.unique_id}'s production status.")
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print(
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f"Warning: Product {product.unique_id} not found in firm "
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f"{firm.unique_id}'s production status. Skipping."
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)
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continue
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# 更新产品状态为干扰状态，并记录干扰时间
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firm.dct_prod_up_prod_stat[product]['p_stat'].append(('D', self.t))
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@ -663,71 +693,71 @@ class MyModel(Model):
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"""
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判断并处理资源的采购。
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"""
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# 存储需要采购资源的企业及其需求
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purchase_material_firms = {}
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material_list = []
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list_seek_material_firm = [] # 每一个收到请求的企业
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# 遍历所有企业，检查资源需求
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for firm in self.company_agents:
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# 如果 firm.R 为 None，跳过处理
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if not firm.R:
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# print(f"Firm {firm.unique_id} has no resource data.")
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if not firm.R: # 跳过没有资源的企业
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continue
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# 处理资源需求
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for sub_list in firm.R:
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if sub_list[1] <= firm.s_r:
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required_material_quantity = firm.S_r - sub_list[1]
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material_list.append([sub_list[0], required_material_quantity])
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purchase_material_firms[firm] = material_list
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# 寻源并发送资源请求
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for material_firm_key, sub_list_values in purchase_material_firms.items():
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for mater_list in sub_list_values:
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result = material_firm_key.seek_material_supply(mater_list[0])
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if result != -1:
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list_seek_material_firm.append(result)
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# 遍历资源列表，检查哪些资源需要补货
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for resource_id, resource_quantity in firm.R:
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if resource_quantity <= firm.s_r: # 如果资源低于阈值，记录需求
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required_quantity = firm.S_r - resource_quantity
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if firm not in purchase_material_firms:
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purchase_material_firms[firm] = []
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purchase_material_firms[firm].append((resource_id, required_quantity))
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if list_seek_material_firm:
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for seek_material_firm in list_seek_material_firm:
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seek_material_firm.handle_material_request(mater_list)
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for R_list in firm.R:
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R_list[1] = firm.S_r
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# 寻找供应商并处理补货
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for firm, material_requests in purchase_material_firms.items():
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for resource_id, required_quantity in material_requests:
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# 寻找供应商
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supplier = firm.seek_material_supply(resource_id)
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if supplier != -1: # 如果找到供应商
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# 供应商处理资源请求
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supplier.handle_material_request([resource_id, required_quantity])
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# 更新当前企业的资源数量
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for resource in firm.R:
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if resource[0] == resource_id:
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resource[1] = firm.S_r
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def _handle_machinery_purchase(self):
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"""
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判断并处理设备的采购。
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"""
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# 存储需要采购设备的企业及其需求
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purchase_machinery_firms = {}
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machinery_list = []
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list_seek_machinery_firm = [] # 每一个收到请求的企业
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# 遍历所有企业，检查设备需求
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for firm in self.company_agents:
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# 处理设备需求
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# 如果 firm.C 为 None，跳过处理
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if not firm.C:
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# print(f"Firm {firm.unique_id} has no equipment to maintain or purchase.")
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if not firm.C: # 跳过没有设备的企业
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continue
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for sub_list in firm.C:
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sub_list[2] -= firm.x # 减少设备残值
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if sub_list[2] <= 0: # 残值小于等于 0
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sub_list[1] -= 1
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required_machinery_quantity = 1
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machinery_list.append([sub_list[0], required_machinery_quantity])
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purchase_machinery_firms[firm] = machinery_list
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# 检查设备残值，记录需要补充的设备
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for equipment in firm.C:
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equipment_id, equipment_quantity, equipment_salvage = equipment
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equipment_salvage -= firm.x # 减少设备残值
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if equipment_salvage <= 0: # 如果残值小于等于 0
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equipment_quantity -= 1
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required_quantity = 1 # 需要补充的设备数量
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if firm not in purchase_machinery_firms:
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purchase_machinery_firms[firm] = []
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purchase_machinery_firms[firm].append((equipment_id, required_quantity))
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# 寻源并发送设备请求
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for machinery_firm, sub_list in purchase_machinery_firms.items():
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for machi_list in sub_list:
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result = machinery_firm.seek_machinery_supply(machi_list[0])
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if result != -1:
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list_seek_machinery_firm.append(result)
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if list_seek_machinery_firm:
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for seek_machinery_firm in list_seek_machinery_firm:
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seek_machinery_firm.handle_machinery_request(machi_list)
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for C_list, C0_list in zip(firm.C, firm.C0):
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C_list[1] = C0_list[1] # 恢复初始值
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C_list[2] = C0_list[2]
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# 寻找供应商并处理设备补充
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for firm, machinery_requests in purchase_machinery_firms.items():
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for equipment_id, required_quantity in machinery_requests:
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# 寻找供应商
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supplier = firm.seek_machinery_supply(equipment_id)
|
||||
if supplier != -1: # 如果找到供应商
|
||||
# 供应商处理设备请求
|
||||
supplier.handle_machinery_request([equipment_id, required_quantity])
|
||||
# 恢复企业的设备数量和残值
|
||||
for equipment, initial_equipment in zip(firm.C, firm.C0):
|
||||
if equipment[0] == equipment_id:
|
||||
equipment[1] = initial_equipment[1] # 恢复数量
|
||||
equipment[2] = initial_equipment[2] # 恢复残值
|
||||
|
||||
def _consume_resources_and_produce(self):
|
||||
"""
|
||||
|
|
@ -736,36 +766,52 @@ class MyModel(Model):
|
|||
k = 0.6 # 资源消耗比例
|
||||
production_increase_ratio = 1.6 # 产品生产比例
|
||||
|
||||
# 遍历每个企业
|
||||
for firm in self.company_agents:
|
||||
# 计算行业的资源消耗
|
||||
consumed_resources = {}
|
||||
for industry in firm.indus_i:
|
||||
# 计算当前行业的资源消耗量
|
||||
consumed_quantity = sum(
|
||||
product[1] * k # product[1] 是产品的数量
|
||||
for product in firm.P
|
||||
if product[0] == industry.unique_id # product[0] 是产品的 ID
|
||||
)
|
||||
# 将计算的消耗量记录到字典中
|
||||
consumed_resources[industry] = consumed_quantity
|
||||
# 计算资源消耗
|
||||
consumed_resources = self._calculate_consumed_resources(firm, k)
|
||||
|
||||
# 消耗资源
|
||||
for resource in firm.R:
|
||||
resource_id, resource_quantity = resource[0], resource[1]
|
||||
for industry, consumed_quantity in consumed_resources.items():
|
||||
if resource_id == industry.unique_id: # 判断资源是否属于该行业
|
||||
resource[1] = max(0, resource_quantity - consumed_quantity)
|
||||
self._consume_resources(firm, consumed_resources)
|
||||
|
||||
# 生产产品
|
||||
for product in firm.P:
|
||||
product_id, product_quantity = product[0], product[1]
|
||||
product[1] = product_quantity * production_increase_ratio
|
||||
self._produce_products(firm, production_increase_ratio)
|
||||
|
||||
# 刷新资源和设备状态
|
||||
firm.refresh_R()
|
||||
firm.refresh_C()
|
||||
firm.refresh_P()
|
||||
|
||||
def _calculate_consumed_resources(self, firm, k):
|
||||
"""
|
||||
计算企业的资源消耗量。
|
||||
"""
|
||||
consumed_resources = {}
|
||||
for industry in firm.indus_i:
|
||||
consumed_quantity = sum(
|
||||
product[1] * k
|
||||
for product in firm.P
|
||||
if product[0] == industry.unique_id
|
||||
)
|
||||
consumed_resources[industry.unique_id] = consumed_quantity
|
||||
return consumed_resources
|
||||
|
||||
def _consume_resources(self, firm, consumed_resources):
|
||||
"""
|
||||
消耗企业的资源。
|
||||
"""
|
||||
for resource in firm.R:
|
||||
resource_id, resource_quantity = resource[0], resource[1]
|
||||
if resource_id in consumed_resources:
|
||||
resource[1] = max(0, resource_quantity - consumed_resources[resource_id])
|
||||
|
||||
def _produce_products(self, firm, production_increase_ratio):
|
||||
"""
|
||||
生产企业的产品。
|
||||
"""
|
||||
for product in firm.P:
|
||||
product[1] *= production_increase_ratio
|
||||
|
||||
def end(self):
|
||||
"""
|
||||
结束模型运行并保存结果。
|
||||
|
|
|
|||
Loading…
Reference in New Issue