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import numpy as np
class Node:
def __init__(self, x, y, demand, earliest_time, latest_time, service_time):
super()
self.x = x
self.y = y
self.demand = demand
self.earliest_time = earliest_time
self.latest_time = latest_time
self.service_time = service_time
class Graph:
def __init__(self, file_path):
super()
# node_num 结点个数
# node_dist_mat 节点之间的距离（矩阵）
# pheromone_mat 节点之间路径上的信息度浓度
self.node_num, self.nodes, self.node_dist_mat = self.create_from_file(file_path)
def create_from_file(self, file_path):
# 从文件中读取服务点、客户的位置
with open(file_path, 'rt') as f:
node_list = list(line.split() for line in f)
node_num = len(node_list)
nodes = list(Node(float(item[0]), float(item[1]), float(item[2]), float(item[3]), float(item[4]), float(item[5])) for item in node_list)
# 创建距离矩阵
node_dist_mat = np.zeros((node_num, node_num))
for i in range(node_num):
node_a = nodes[i]
for j in range(i, node_num):
node_b = nodes[j]
node_dist_mat[i][j] = Graph.calculate_dist(node_a, node_b)
node_dist_mat[j][i] = node_dist_mat[i][j]
return node_num, nodes, node_dist_mat
@staticmethod
def calculate_dist(node_a, node_b):
return np.linalg.norm((node_a.x - node_b.x, node_a.y - node_b.y))
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