第十一章:图论part10
今天大家会感受到 Bellman_ford 算法系列在不同场景下的应用。
建议依然是:一刷的时候,能理解 原理,知道Bellman_ford 解决不同场景的问题 ,照着代码随想录能抄下来代码就好,就算达标。
二刷的时候自己尝试独立去写,三刷的时候 才能有一定深度理解各个最短路算法。
Bellman_ford 队列优化算法(又名SPFA)
import collections
def main():
n, m = map(int, input().strip().split())
edges = [[] for _ in range(n + 1)]
for _ in range(m):
src, dest, weight = map(int, input().strip().split())
edges[src].append([dest, weight])
minDist = [float("inf")] * (n + 1)
minDist[1] = 0
que = collections.deque([1])
visited = [False] * (n + 1)
visited[1] = True
while que:
cur = que.popleft()
visited[cur] = False
for dest, weight in edges[cur]:
if minDist[cur] != float("inf") and minDist[cur] + weight < minDist[dest]:
minDist[dest] = minDist[cur] + weight
if visited[dest] == False:
que.append(dest)
visited[dest] = True
if minDist[-1] == float("inf"):
return "unconnected"
return minDist[-1]
if __name__ == "__main__":
print(main())
bellman_ford之判断负权回路
import sys
def main():
input = sys.stdin.read
data = input().split()
index = 0
n = int(data[index])
index += 1
m = int(data[index])
index += 1
grid = []
for i in range(m):
p1 = int(data[index])
index += 1
p2 = int(data[index])
index += 1
val = int(data[index])
index += 1
# p1 指向 p2,权值为 val
grid.append([p1, p2, val])
start = 1 # 起点
end = n # 终点
minDist = [float('inf')] * (n + 1)
minDist[start] = 0
flag = False
for i in range(1, n + 1): # 这里我们松弛n次,最后一次判断负权回路
for side in grid:
from_node = side[0]
to = side[1]
price = side[2]
if i < n:
if minDist[from_node] != float('inf') and minDist[to] > minDist[from_node] + price:
minDist[to] = minDist[from_node] + price
else: # 多加一次松弛判断负权回路
if minDist[from_node] != float('inf') and minDist[to] > minDist[from_node] + price:
flag = True
if flag:
print("circle")
elif minDist[end] == float('inf'):
print("unconnected")
else:
print(minDist[end])
if __name__ == "__main__":
main()
bellman_ford之单源有限最短路
#include <iostream>
#include <vector>
#include <queue>
#include <list>
#include <climits>
using namespace std;
struct Edge { //邻接表
int to; // 链接的节点
int val; // 边的权重
Edge(int t, int w): to(t), val(w) {} // 构造函数
};
int main() {
int n, m, p1, p2, val;
cin >> n >> m;
vector<list<Edge>> grid(n + 1); // 邻接表
// 将所有边保存起来
for(int i = 0; i < m; i++){
cin >> p1 >> p2 >> val;
// p1 指向 p2,权值为 val
grid[p1].push_back(Edge(p2, val));
}
int start, end, k;
cin >> start >> end >> k;
k++;
vector<int> minDist(n + 1 , INT_MAX);
vector<int> minDist_copy(n + 1); // 用来记录每一次遍历的结果
minDist[start] = 0;
queue<int> que;
que.push(start); // 队列里放入起点
int que_size;
while (k-- && !que.empty()) {
vector<bool> visited(n + 1, false); // 每一轮松弛中,控制节点不用重复入队列
minDist_copy = minDist;
que_size = que.size();
while (que_size--) {
int node = que.front(); que.pop();
for (Edge edge : grid[node]) {
int from = node;
int to = edge.to;
int price = edge.val;
if (minDist[to] > minDist_copy[from] + price) {
minDist[to] = minDist_copy[from] + price;
if(visited[to]) continue; // 不用重复放入队列,但需要重复松弛,所以放在这里位置
visited[to] = true;
que.push(to);
}
}
}
}
if (minDist[end] == INT_MAX) cout << "unreachable" << endl;
else cout << minDist[end] << endl;
}