dijkstra

模板提 P3381 【模板】最小费用最大流 个人简述 首先呢，dijkstra算法求费用流是不如spfa求费用流的，因为这个题目不开O2优化，就过不去.... 那么我们为什么要用这个算法呢？个人认为确实没什么用....还是用spfa或者zkw求费用流吧 总所周知，dijkstra是不能跑有负环的图的，而我们在求最小费用流的过程中一般会存在负环（反边的存在），因此我通过引入势的概念，将图的边用 e' 代替，其中 e' = e + h[u] - h[v] ，h[i]代表i点的势，这样的话，将新的图中的s-t路径的长度减去常数h[s] - h[t] ，得到的即为原图中对应路径的长度，因此新图和原图中的最短路是一致的。 因为dijkstra只实用于无负环的图，所以我们需要选取合适的势，将使得新图的每一条边的费用 cost[e] >= 0，我们就可以用dijkstra算法求最小费用流了。 代码区 #pragma GCC optimize(2) //O2优化，不开过不去... #include<iostream> #include<cstdio> #include<algorithm> #include<cstring> #include<queue> #include<string> #include<fstream> #include<vector> #include<stack>

Can somebody tell me why Dijkstra's algorithm for single source shortest path assumes that the edges must be non-negative. I am talking about only edges not the negative weight cycles. Recall that in Dijkstra's algorithm, once a vertex is marked as "closed" (and out of the open set) - the algorithm found the shortest path to it , and will never have to develop this node again - it assumes the path developed to this path is the shortest. But with negative weights - it might not be true. For example: A / \ / \ / \ 5 2 / \ B--(-10)-->C V={A,B,C} ; E = {(A,C,2), (A,B,5), (B,C,-10)} Dijkstra from A

I am trying to understand why Dijkstra's algorithm will not work with negative weights. Reading an example on Shortest Paths , I am trying to figure out the following scenario: 2 A-------B \ / 3 \ / -2 \ / C From the website: Assuming the edges are all directed from left to right, If we start with A, Dijkstra's algorithm will choose the edge (A,x) minimizing d(A,A)+length(edge), namely (A,B). It then sets d(A,B)=2 and chooses another edge (y,C) minimizing d(A,y)+d(y,C); the only choice is (A,C) and it sets d(A,C)=3. But it never finds the shortest path from A to B, via C, with total length 1.

真的只想说一点：细节！！！！！！delet的top--在哪写，还有down 里面的while(s<=top) 不要写成<=n!!!!!!! s<top不要写成 s<n 我调了一个上午while(s<top)调了将近两个小时，结果忘改后边那个，，又改了一个小时，心态炸了，怎么老犯sd错误inline void swp(int &x,int &y){x^=y,y^=x,x^=y;} inline void up(int p) { while(p>1){ if(heap[p]<heap[p>>1]) swp(heap[p],heap[p>>1]),swp(pn[p],pn[p>>1]); else break; p>>=1; } } inline void down(int p){ int s=(p<<1); while(s<=top){ if(s<top&&heap[s]>heap[s+1]) ++s; if(heap[s]<heap[p]) {swp(heap[s],heap[p]),swp(pn[s],pn[p]);} else break; p=s,s=(p<<1); } } inline void insert(int x,int y){ heap[++top]=x,pn[top]=y,up(top); } inline void delet(){ heap[1]=heap

Description： BIT has recently taken delivery of their new supercomputer, a 32 processor Apollo Odyssey distributed shared memory machine with a hierarchical communication subsystem. Valentine McKee's research advisor, Jack Swigert, has asked her to benchmark the new system. ``Since the Apollo is a distributed shared memory machine, memory access and communication times are not uniform,'' Valentine told Swigert. ``Communication is fast between processors that share the same memory subsystem, but it is slower between processors that are not on the same subsystem. Communication between the Apollo