问题描述
我需要用下面的算法计算总路径成本
此代码查找两个节点之间的最短或最佳路径。 这段代码不是我写的，我实际上是在尝试学习明智的搜索算法以及它们是如何工作的。我们将不胜感激。
我还附上了一张图表图片，其中包含此代码中使用的实际值和启发式值
from collections import deque
class Graph:
def __init__(self,adjacency_list):
self.adjacency_list = adjacency_list
def get_neighbors(self,v):
return self.adjacency_list[v]
# heuristic function with values for all nodes
def h(self,n):
H = {
'oradea': 380,'zerind': 374,'sibiu': 253,'arad': 366,'timisoara': 329,'lugoj': 244,'mehadia': 241,'dobreta': 242,'craiova': 160,'rimnicu vilcea': 193,'pitesti': 10,'fagaras': 176,'bucharest': 0,'giurgiu': 77,'urziceni': 80,'vaslui': 199,'lasi': 226,'neamt': 234,'hirsova': 151,'eforie': 161
}
return H[n]
def a_star_algorithm(self,start_node,stop_node):
# open_list is a list of nodes which have been visited,but who's neighbors
# haven't all been inspected,starts off with the start node
# closed_list is a list of nodes which have been visited
# and who's neighbors have been inspected
open_list = set([start_node])
closed_list = set([])
# g contains current distances from start_node to all other nodes
# the default value (if it's not found in the map) is +infinity
g = {}
g[start_node] = 0
# parents contains an adjacency map of all nodes
parents = {}
parents[start_node] = start_node
while len(open_list) > 0:
n = None
# find a node with the lowest value of f() - evaluation function
for v in open_list:
if n == None or g[v] + self.h(v) < g[n] + self.h(n):
n = v;
if n == None:
print('Path does not exist!')
return None
# if the current node is the stop_node
# then we begin reconstruction the path from it to the start_node
if n == stop_node:
reconst_path = []
while parents[n] != n:
reconst_path.append(n)
n = parents[n]
reconst_path.append(start_node)
reconst_path.reverse()
print('Path found: {}'.format(reconst_path))
return reconst_path
# for all neighbors of the current node do
for (m,weight) in self.get_neighbors(n):
# if the current node isn't in both open_list and closed_list
# add it to open_list and note n as it's parent
if m not in open_list and m not in closed_list:
open_list.add(m)
parents[m] = n
g[m] = g[n] + weight
# otherwise,check if it's quicker to first visit n,then m
# and if it is,update parent data and g data
# and if the node was in the closed_list,move it to open_list
else:
if g[m] > g[n] + weight:
g[m] = g[n] + weight
parents[m] = n
if m in closed_list:
closed_list.remove(m)
open_list.add(m)
# remove n from the open_list,and add it to closed_list
# because all of his neighbors were inspected
open_list.remove(n)
closed_list.add(n)
print('Path does not exist!')
return None
# adjacency list (or rather map)
adjacency_list = {
'oradea': [('zerind',71),('sibiu',151)],'zerind': [('oradea',('arad',75)],'sibiu': [('oradea',151),140),('fagaras',99),('rimnicu vilcea',80)],'arad': [('zerind',('timisoara',118),140)],'timisoara': [('arad',('lugoj',111)],'lugoj': [('timisoara',111),('mehadia',70)],'mehadia': [('lugoj',70),('dobreta','dobreta': [('mehadia',75),('craiova',120)],'craiova': [('dobreta',120),('pitesti',138),148)],'rimnicu vilcea': [('craiova',148),80),97)],'pitesti': [('craiova',97),('bucharest',101)],'fagaras': [('sibiu',211)],'bucharest': [('pitesti',101),211),('giurgiu',90),('urziceni',85)],'giurgiu': [('bucharest',90)],'urziceni': [('bucharest',85),('hirsova',98),('vaslui',142)],'vaslui': [('urziceni',142),('lasi',92)],'lasi': [('vaslui',92),('neamt',87)],'neamt': [('lasi','hirsova': [('urziceni',('eforie',86)],'eforie': [('hirsova',86)]
}
graph1 = Graph(adjacency_list)
graph1.a_star_algorithm('oradea','pitesti')
解决方法
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