def borne_sup(data):
solution = Solution(data.graph)
solution.name = 'sup'
solution.num_evac_nodes = data.num_evac_nodes
solution.method = 'computed ' + solution.name
start_time = time()
# start each evacuation one by one
start_evac = 0
for (node_id, node_data) in data.graph.nodes(data=True):
# to get only the evac nodes
if 'population' in node_data:
solution.evac_nodes[str(node_id)] = EvacNode(
node_id, int(node_data['max_rate']), start_evac)
path = node_data['path']
# add each route lenght to duration
for a, b in zip([node_id] + path, path):
start_evac += int(data.graph[a][b]['lenght'])
solution.calc_time = time() - start_time
solution.calc_obj()
solution.create_timeline()
solution.check_valid()
return solution
def borne_inf(data):
solution = Solution(data.graph)
solution.name = 'inf'
solution.num_evac_nodes = data.num_evac_nodes
solution.method = 'computed' + solution.name
start_time = time()
# for each evac node, set start date to 0 and max rate
for (node_id, node_data) in data.graph.nodes(data=True):
# to get only the evac nodes
if 'population' in node_data:
solution.evac_nodes[str(node_id)] = EvacNode(
node_id, int(node_data['max_rate']), 0)
solution.calc_time = time() - start_time
solution.calc_obj()
solution.create_timeline()
solution.check_valid()
return solution
#!/usr/bin/python3
import matplotlib.pyplot as plt
import networkx as nx
from Data import Data
from Solution import Solution
data = Data()
data.read_file('Instances/graphe25.full')
plt.subplot(111)
pos = nx.spring_layout(data.graph, scale=0.5)
nx.draw_networkx(data.graph, pos=pos)
nx.draw_networkx_edge_labels(data.graph,
pos=pos,
edge_labels=data.get_edges_labels(),
label_pos=0.5)
plt.show()
for ext in ['inf', 'sol', 'sup']:
solution = Solution(data.graph)
solution.read_file('Solutions/graphe25.' + ext)
solution.calc_obj()
print(ext + ' cal_obj:', solution.calc_obj())
solution.create_timeline()
solution.display_timeline()
print(ext + ' ratesOk:', solution.verify_rates())
print(ext + ' dueDateOk:', solution.verify_duedates())
