Original link: http://www.cnblogs.com/Jason-Damon/archive/2012/04/21/2460850.htmlExcerpt from Baidu EncyclopediaThe Bellman-ford algorithm is a single-source shortest path algorithm with negative weights, which is very inefficient, but the code is easy to write. That is, the continuous relaxation (relaxation), each slack to update each edge, if the n-1 can be updated after the relaxation, then the picture has a negative ring (that is, the negative pow
notifications to Slack. @ Slack command receives a Slack hook URL, a channel name, and the message content you want to send:
@after @slack('hook', 'channel', 'message')@endafter
You can create an Incoming WebHooks on the Slack website to obtain the webhook URL. The hook
be achieved by O (N^3). We give each Y vertex a "slack" function slack, which is initialized to infinity each time we start looking for an augmented path. While looking for an augmented path, when checking for edges (XI,YJ), if it is not in the equal sub-graph, let slack[j] be the smaller value of the original value and Lx[i] + ly[j]-w[xi,yj]. This way, when you
Test instructions: N students arranged to M dormitory, each student to the dormitory has a rating, positive, 0, negative, now the evaluation is negative, can not let this student go to this room, ask how to arrange to let all the students live in the dormitory and the most evaluation.Idea: When building the weight of a graph, filter out negative edges.#include #include #include #include #include #include #include #include #include #include #include #include #define Lson (rt#define Rson (rt#defin
to match the number of points /* IF (! Findpath (i)) return false; */}//return true; if(Ans = = N)printf("T-shirts rock!\n");Else printf("I ' d rather not wear a shirt anyway...\n");}The best matching--km algorithm of binary graph:#include #include #include #include using namespace STD;Const intMAXN = the;Const intINF =0xffffff0;intN,nx,ny;intLINK[MAXN],LX[MAXN],LY[MAXN],SLACK[MAXN];intVISX[MAXN],VISY[MAXN];//MarkintMAP[MAXN][
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Article, where the information may have evolved or changed.
Objective
In the previous article, we simply introduced the deployment of drone. The next step is to introduce the official documents as well as the plugins I used in the actual work. This article, is mainly a complete drone demo. Pipeline includes the Git clone pull code, the go build build, the Docker image is generated and pushed to the harbor,notify notification. On the notice, the official plug-ins are some of
If a thing, you do not love him, perhaps because you fear it, dare not to touch him, so devote less time. Muddle through the living, muddle through life, will slack off, and is once the opportunity to slack, no opportunity will also create opportunities to slack off, and the first big law is "slack people will never su
the Y-square point):Neither In this way, the original viable edges in the diagram are still viable after this step of the modification, and the previously infeasible edges may now become viable edges. So how much should the value of D take? Obviously, the entire point mark can not lose the feasibility, that is, for the above after this step, at least one feasible edge will be added to the figure. (5) After the modification, continue to the X-side point Dfs augmentation, if it fails, continue to
HDU_2813
To avoid time-out when reading data, hash can be used for processing, and then non-Repeated names can be taken out for a vertex, then use the KM algorithm to find the optimal matching for the bipartite graph.
#include#include#include#define MAXD 210#define MAXM 40010#define INF 1000000000#define HASH 10007int headL[HASH], nextL[MAXM], headC[HASH], nextC[MAXM];int N, M, K, G[MAXD][MAXD], yM[MAXD], MAX;int A[MAXD], B[MAXD], slack[MAXD];int vis
HDU_1533
The shortest distance between people and houses is the distance between Manhattan. After creating the image, apply the KM algorithm to obtain the optimal matching of the Bipartite Graph.
#include#include#include#define MAXD 110#define MAX 10010#define INF 1000000000int N, hx[MAXD], hy[MAXD], px[MAXD], py[MAXD];int a[MAXD][MAXD], G[MAXD][MAXD], yM[MAXD];int A[MAXD], B[MAXD], slack, visx[MAXD], visy[MAXD];char b[MAXD];int init(){int i, j, k, n
HDU_3772
We can split a string into two vertices to represent the inbound and outbound degrees, and then use the KM algorithm to perform Optimal Matching for the bipartite graph.
#include#include#define MAXD 210#define INF 1000000000char b[MAXD][1010];int G[MAXD][MAXD] , yM[MAXD], N;int A[MAXD], B[MAXD], slack;int visx[MAXD], visy[MAXD];int check(char *str1, char *str2){int i, j, num = 0; i =strlen(str1) - 1;for(j = 0; str1[i] == str2[j] i >= 0
Uva_000046
This topic can be done with the minimum cost and the maximum flow. In order to review the optimal matching of the bipartite graph, we wrote a KM program.
At first, because I had not processed the double KM before, I was going to multiply the decimal number by a certain power of 10 into an integer, but I found that WA was always there, and then I simply wrote it using double, and then the AC.
#include#include#include#define MAXD 30#define INF 1000000000int N, M, xM[MAXD], yM[MAXD] ,vis
students as X-sets, M-rooms as the Y-set, and then call the KM algorithm to be able. 1#include 2#include 3#include 4#include 5#include 6#include 7 #defineINF 0x7fffffff8 using namespacestd;9 Const intmaxn= -+Ten;Ten One intn,m; A intLX[MAXN],LY[MAXN],VISX[MAXN],VISY[MAXN]; - intLINK[MAXN],SLACK[MAXN],W[MAXN][MAXN]; - the intDfsintx) - { -visx[x]=1; - for(inty=1; yif(w[x][y]!=-1) + { - if(Visy[y])Continue; + intt=lx[x]+ly[y]
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