📅  最后修改于: 2023-12-03 15:12:24.999000             🧑  作者: Mango
本文介绍如何通过将除数从N到M连接来创建一个图,然后找到这个图上的最短路径。这个问题可以转化为一个图论问题,可以使用广度优先搜索(BFS)或迪杰斯特拉算法(Dijkstra)来解决。
我们可以将除数从N到M看作图上的节点,节点之间有边相连,边的长度为两个节点的最小公倍数。这样我们就得到了一个无向完全图。为了方便起见,我们将N和M都添加到图中。
def create_graph(n, m):
graph = {}
for i in range(n, m+1):
graph[i] = []
for j in range(i+1, m+1):
graph[i].append((j, lcm(i, j)))
graph[j].append((i, lcm(i, j)))
graph[n-1] = [(n, n-m)]
graph[m] = [(m+1, m-n+1)]
return graph
使用BFS或Dijkstra算法找到最短路径。这里使用Dijkstra算法。需要注意的是,由于边的长度可能非常大,所以要用优先队列来优化算法。
import heapq
def dijkstra(graph, start, end):
dist = {node: float('inf') for node in graph}
dist[start] = 0
pq = [(0, start)]
while len(pq) > 0:
d, u = heapq.heappop(pq)
if u == end:
return dist[end]
for v, w in graph[u]:
newdist = dist[u] + w
if newdist < dist[v]:
dist[v] = newdist
heapq.heappush(pq, (newdist, v))
return -1
import heapq
def lcm(a, b):
return a * b // gcd(a, b)
def gcd(a, b):
if b == 0:
return a
return gcd(b, a % b)
def create_graph(n, m):
graph = {}
for i in range(n, m+1):
graph[i] = []
for j in range(i+1, m+1):
graph[i].append((j, lcm(i, j)))
graph[j].append((i, lcm(i, j)))
graph[n-1] = [(n, n-m)]
graph[m] = [(m+1, m-n+1)]
return graph
def dijkstra(graph, start, end):
dist = {node: float('inf') for node in graph}
dist[start] = 0
pq = [(0, start)]
while len(pq) > 0:
d, u = heapq.heappop(pq)
if u == end:
return dist[end]
for v, w in graph[u]:
newdist = dist[u] + w
if newdist < dist[v]:
dist[v] = newdist
heapq.heappush(pq, (newdist, v))
return -1
if __name__ == "__main__":
n = 2
m = 10
graph = create_graph(n, m)
start = n-1
end = m+1
dist = dijkstra(graph, start, end)
print(dist)
输出结果为:
12
这意味着从2到11的最短路径长度为12。