file1.py

client = {
    0: {"name": "Client 0", "demand": 120, "covered by": [10000, 10001, 10004]},
    1: {"name": "Client 1", "demand": 100, "covered by": [10000]},
    2: {"name": "Client 2", "demand": 80, "covered by": [10002, 10003, 10004]},
    3: {"name": "Client 3", "demand": 140, "covered by": [10002, 10005]},
    4: {"name": "Client 4", "demand": 170, "covered by": [10002, 10005]},
    5: {"name": "Client 5", "demand": 100, "covered by": [10000, 10003]},
    6: {"name": "Client 6", "demand": 120, "covered by": [10002, 10003, 10004]},
    7: {"name": "Client 7", "demand": 90, "covered by": [10001, 10004]},
    8: {"name": "Client 8", "demand": 50, "covered by": [10001, 10004, 10005]},
}

facility = {
    10000: {"name": "Facility 0", "capacity": 200, "cover": [0, 1, 5]},
    10001: {"name": "Facility 1", "capacity": 150, "cover": [0, 7, 8]},
    10002: {"name": "Facility 2", "capacity": 240, "cover": [2, 3, 4, 6]},
    10003: {"name": "Facility 3", "capacity": 210, "cover": [2, 5, 6]},
    10004: {"name": "Facility 4", "capacity": 120, "cover": [0, 2, 6, 7, 8]},
    10005: {"name": "Facility 5", "capacity": 200, "cover": [3, 4, 8]},
}

file2.py

import matplotlib.pyplot as plt
import networkx as nx

fig = plt.figure(figsize=(6, 6))
ax = plt.subplot(111)
ax.set_title("CSCLP", fontsize=18)

# グラフの定義
G = nx.DiGraph()

# client ノードの登録
client_list = []
client_labels = {}
for i in client:
    G.add_node(i)
    client_list.append(i)
    client_labels[i] = client[i]["demand"]

# facility ノードの登録
facility_list = []
facility_labels = {}
for j in facility:
    G.add_node(j)
    facility_list.append(j)
    facility_labels[j] = facility[j]["capacity"]
    
# エッジの登録
for i in client:
    for j in client[i]["covered by"]:
        G.add_edge(i,j)

# 座標情報の生成
pos = nx.circular_layout(G)

# clientノードの描画
client_node_size = [ client[i]["demand"]*5 for i in client ]

nx.draw_networkx_nodes(G, pos, nodelist=client_list, node_color="r", alpha=0.6, node_size=client_node_size)
nx.draw_networkx_labels(G, pos, labels=client_labels)

# facilityノードの描画
facility_node_size = [ facility[j]["capacity"]* 5 for j in facility ]

nx.draw_networkx_nodes(G, pos, nodelist=facility_list, node_color="b", alpha=0.6, node_size=facility_node_size)
nx.draw_networkx_labels(G, pos, labels=facility_labels)

# エッジの描画
nx.draw_networkx_edges(G, pos, alpha=0.4, edge_color="C")

plt.axis("off")
plt.show()

file3.py

from gurobipy import *

# モデルの構築
m = Model()

# 決定変数
x = {}
y = {}

# 決定変数の定義
for i in client:
    for j in facility:
        x[(i,j)] = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="x%d,%d" % (i,j))
        y[j] = m.addVar(vtype=GRB.BINARY, name="x%d" % j)
        
m.update()

# 制約条件の定義
for i in client:
    m.addConstr( quicksum(x[(i,j)] for j in client[i]["covered by"]) >= 1 )
    
for j in facility:
    m.addConstr( quicksum(client[i]["demand"]*x[(i,j)] for i in client) - facility[j]["capacity"]*y[j] <= 0 )    

# 目的関数の定義
m.setObjective( quicksum( y[j] for j in facility ), GRB.MINIMIZE )

# 計算の実行
m.optimize()

file4.py

import matplotlib.pyplot as plt
import networkx as nx

fig = plt.figure(figsize=(6, 6))
ax = plt.subplot(111)
ax.set_title("CSCLP result", fontsize=18)

# グラフの定義
G = nx.DiGraph()

# client ノードの登録
client_list = []
client_labels = {}
for i in client:
    G.add_node(i)
    client_list.append(i)
    client_labels[i] = client[i]["demand"]

# facility ノードの登録
facility_list = []
facility_labels = {}
for j in facility:
    if y[j].x == 1:
        G.add_node(j)
        facility_list.append(j)
        facility_labels[j] = facility[j]["capacity"]

# エッジを追加
for i in client:
    for j in facility:
        if x[(i,j)].x > 0:
            G.add_edge(i, j, weight = x[(i,j)].x * client[i]["demand"] * 0.005)


# 座標情報の生成
pos = nx.circular_layout(G)

# clientノードの描画
client_node_size = [ client[i]["demand"]*5 for i in client ]

nx.draw_networkx_nodes(G, pos, nodelist=client_list, node_color="r", alpha=0.6, node_size=client_node_size)
nx.draw_networkx_labels(G, pos, labels=client_labels)

# facilityノードの描画
facility_node_size = [ facility[j]["capacity"]*5 for j in facility ]
nx.draw_networkx_nodes(G, pos, nodelist=facility_list, node_color="b", alpha=0.6, node_size=facility_node_size)
nx.draw_networkx_labels(G, pos, labels=facility_labels)

# エッジの描画
edge_width = [ d["weight"]*10 for (u,v,d) in G.edges(data=True) ]
nx.draw_networkx_edges(G, pos, alpha=0.4, edge_color="C", width=edge_width)

plt.axis("off")
plt.show()

file5.py

client = {
    0: {"name": "Client 0", "demand": 120, "covered by": [10000, 10001, 10004]},
    1: {"name": "Client 1", "demand": 100, "covered by": [10000]},
    2: {"name": "Client 2", "demand": 80, "covered by": [10002, 10003, 10004]},
    3: {"name": "Client 3", "demand": 140, "covered by": [10002, 10005]},
    4: {"name": "Client 4", "demand": 170, "covered by": [10002, 10005]},
    5: {"name": "Client 5", "demand": 100, "covered by": [10000, 10003]},
    6: {"name": "Client 6", "demand": 120, "covered by": [10002, 10003, 10004]},
    7: {"name": "Client 7", "demand": 90, "covered by": [10001, 10004]},
    8: {"name": "Client 8", "demand": 50, "covered by": [10001, 10004, 10005]},
}

facility = {
    10000: {"name": "Facility 0", "capacity": 200, "cover": [0, 1, 5]},
    10001: {"name": "Facility 1", "capacity": 150, "cover": [0, 7, 8]},
    10002: {"name": "Facility 2", "capacity": 240, "cover": [2, 3, 4, 6]},
    10003: {"name": "Facility 3", "capacity": 210, "cover": [2, 5, 6]},
    10004: {"name": "Facility 4", "capacity": 120, "cover": [0, 2, 6, 7, 8]},
    10005: {"name": "Facility 5", "capacity": 200, "cover": [3, 4, 8]},
}

p = 3

file6.py

from gurobipy import *

# モデルの構築
m = Model()

# 決定変数
x = {}
y = {}
u = {}

# 決定変数の定義
for i in client:
    for j in facility:
        x[(i,j)] = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="x%d,%d" % (i,j))
        y[j] = m.addVar(vtype=GRB.BINARY, name="x%d" % j)
        u[i] = m.addVar(lb=0, vtype=GRB.CONTINUOUS, name="u%d" % i)
        
m.update()

# 制約条件の定義
for i in client:
    m.addConstr( quicksum(x[(i,j)] for j in client[i]["covered by"]) + u[i] == 1 )
    
for j in facility:
    m.addConstr( quicksum(client[i]["demand"]*x[(i,j)] for i in facility[j]["cover"]) - facility[j]["capacity"]*y[j] <= 0 )   
    
m.addConstr( quicksum(y[j] for j in facility) == p )

# 目的関数の定義
m.setObjective( quicksum( client[i]["demand"]*u[i] for i in client ), GRB.MINIMIZE )

# 計算の実行
m.optimize()

file7.py

import matplotlib.pyplot as plt
import networkx as nx

fig = plt.figure(figsize=(6, 6))
ax = plt.subplot(111)
ax.set_title("CMCLP result", fontsize=18)

# グラフの定義
G = nx.DiGraph()

# client ノードの登録
client_list = []
client_labels = {}
for i in client:
    G.add_node(i)
    client_list.append(i)
    client_labels[i] = client[i]["demand"]

# facility ノードの登録
facility_list = []
facility_labels = {}
for j in facility:
    if y[j].x == 1:
        G.add_node(j)
        facility_list.append(j)
        facility_labels[j] = facility[j]["capacity"]

# エッジを追加
for i in client:
    for j in facility:
        if x[(i,j)].x > 0:
            G.add_edge(i, j, weight = x[(i,j)].x * client[i]["demand"] * 0.005)


# 座標情報の生成
pos = nx.circular_layout(G)

# clientノードの描画
client_node_size = [ client[i]["demand"]*5 for i in client ]

nx.draw_networkx_nodes(G, pos, nodelist=client_list, node_color="r", alpha=0.6, node_size=client_node_size)
nx.draw_networkx_labels(G, pos, labels=client_labels)

# facilityノードの描画
facility_node_size = [ facility[j]["capacity"]*5 for j in facility ]
nx.draw_networkx_nodes(G, pos, nodelist=facility_list, node_color="b", alpha=0.6, node_size=facility_node_size)
nx.draw_networkx_labels(G, pos, labels=facility_labels)

# エッジの描画
edge_width = [ d["weight"]*10 for (u,v,d) in G.edges(data=True) ]
nx.draw_networkx_edges(G, pos, alpha=0.4, edge_color="C", width=edge_width)

plt.axis("off")
plt.show()