1、有向无环图(DAG图)
用二叉树表示表达式(空间耗费过多)------->有向无环图表示(可以实现相同子式的共享,节省存储空间)。
有向图检查环比无向图的复杂许多。
AOV网络:强调以顶点作为活动的网络图;--->拓扑排序
AOE网络:强调以边作为活动的网络图; --->关心边上的权值信息--->关键路径
2、拓扑排序
不关心所花费的代价,只关心当前的工作完成没有。
由某个集合上的一个偏序得到该集合上的一个全序, (偏序,全序,离散数学上的);
前提:(1)、有向无环图;(2)、结果不唯一;
思想:(1)、从任何一个没有入度的顶点作为起始;
(2)、排完该顶点后,删除该顶点,连边一起删了(也就是将其它顶点的入度-1);
(3)、每次只找没有入度的进行排序(有好几个入度为0时,就造成了拓扑排序不唯一);
模型分析:
3、拓扑排序算法
均由C++实现(用邻接矩阵):
templatevoid GraphMtx ::TopoLogicalSort(){ //拓扑排序 int n = Graph ::getCurVertex(); int *count = new int[n]; for(int i = 0; i < n; i++){ //count数组记载入度 count[i] = 0; } for(i = 0; i < n; i++){ for(int j = 0; j < n; j++){ if(edge[i][j] == 1){ count[j]++; //计算每个顶点的入度 } } } int top = -1; for(i = 0; i < n; i++){ if(count[i] == 0){ //模拟入栈push() count[i] = top; top = i; } } int v, w; for(i = 0; i < n; i++){ if(top == -1){ //有环图,直接返回; return; }else{ v = top; //模拟出栈pop() top = count[top]; printf("%c-->", getValue(v)); w = getFirstNeighbor(getValue(v)); while(w != -1){ if(--count[w] == 0){ count[w] = top; //删除了一个顶点,统计一遍,满足入栈push() top = w; } w = getNextNeighbor(getValue(v), getValue(w)); } } } cout<<"Over."< 4、完整代码、测试代码、测试结果
(1)、完整代码
#ifndef _GRAPH_H_ #define _GRAPH_H_ #include#include using namespace std; #define VERTEX_DEFAULT_SIZE 10 #define MAX_COST 0x7FFFFFFF template class Graph{ public: bool isEmpty()const{ return curVertices == 0; } bool isFull()const{ if(curVertices >= maxVertices || curEdges >= curVertices*(curVertices-1)/2) return true; //图满有2种情况:(1)、当前顶点数超过了最大顶点数,存放顶点的空间已满 return false; //(2)、当前顶点数并没有满,但是当前顶点所能达到的边数已满 } int getCurVertex()const{ return curVertices; } int getCurEdge()const{ return curEdges; } public: virtual bool insertVertex(const Type &v) = 0; //插入顶点 virtual bool insertEdge(const Type &v1, const Type &v2, E cost) = 0; //插入边 virtual bool removeVertex(const Type &v) = 0; //删除顶点 virtual bool removeEdge(const Type &v1, const Type &v2) = 0; //删除边 virtual int getFirstNeighbor(const Type &v) = 0; //得到第一个相邻顶点 virtual int getNextNeighbor(const Type &v, const Type &w) = 0; //得到下一个相邻顶点 public: virtual int getVertexIndex(const Type &v)const = 0; //得到顶点下标 virtual void showGraph()const = 0; //显示图 virtual Type getValue(int index)const = 0; public: virtual void DFS(const Type &v) = 0; virtual void BFS(const Type &v) = 0; protected: int maxVertices; //最大顶点数 int curVertices; //当前顶点数 int curEdges; //当前边数 }; template class GraphMtx : public Graph { //邻接矩阵继承父类矩阵 #define maxVertices Graph ::maxVertices //因为是模板,所以用父类的数据或方法都得加上作用域限定符 #define curVertices Graph ::curVertices #define curEdges Graph ::curEdges public: GraphMtx(int vertexSize = VERTEX_DEFAULT_SIZE){ //初始化邻接矩阵 maxVertices = vertexSize > VERTEX_DEFAULT_SIZE ? vertexSize : VERTEX_DEFAULT_SIZE; vertexList = new Type[maxVertices]; //申请顶点空间 for(int i = 0; i < maxVertices; i++){ //都初始化为0 vertexList[i] = 0; } edge = new int*[maxVertices]; //申请边的行 for(i = 0; i < maxVertices; i++){ //申请列空间 edge[i] = new int[maxVertices]; } for(i = 0; i < maxVertices; i++){ //赋初值为0 for(int j = 0; j < maxVertices; j++){ if(i != j){ edge[i][j] = MAX_COST; //初始化时都赋为到其它边要花的代价为无穷大。 }else{ edge[i][j] = 0; //初始化时自己到自己认为花费为0 } } } curVertices = curEdges = 0; //当前顶点和当前边数 } GraphMtx(Type (*mt)[4], int sz){ //通过已有矩阵的初始化 int e = 0; //统计边数 maxVertices = sz > VERTEX_DEFAULT_SIZE ? sz : VERTEX_DEFAULT_SIZE; vertexList = new Type[maxVertices]; //申请顶点空间 for(int i = 0; i < maxVertices; i++){ //都初始化为0 vertexList[i] = 0; } edge = new int*[maxVertices]; //申请边的行 for(i = 0; i < maxVertices; i++){ //申请列空间 edge[i] = new Type[maxVertices]; } for(i = 0; i < maxVertices; i++){ //赋初值为矩阵当中的值 for(int j = 0; j < maxVertices; j++){ edge[i][j] = mt[i][j]; if(edge[i][j] != 0){ e++; //统计列的边数 } } } curVertices = sz; curEdges = e/2; } ~GraphMtx(){} public: bool insertVertex(const Type &v){ if(curVertices >= maxVertices){ return false; } vertexList[curVertices++] = v; return true; } bool insertEdge(const Type &v1, const Type &v2, E cost){ int maxEdges = curVertices*(curVertices-1)/2; if(curEdges >= maxEdges){ return false; } int v = getVertexIndex(v1); int w = getVertexIndex(v2); if(v==-1 || w==-1){ cout<<"edge no exit"< ::getCurVertex(); bool *visit = new bool[n]; for(int i = 0; i < n; i++){ visit[i] = false; } DFS(v, visit); delete []visit; } void BFS(const Type &v){ int n = Graph ::getCurVertex(); bool *visit = new bool[n]; for(int i = 0; i < n; i++){ visit[i] = false; } cout< "; int index = getVertexIndex(v); visit[index] = true; queue q; //队列中存放的是顶点下标; q.push(index); int w; while(!q.empty()){ index = q.front(); q.pop(); w = getFirstNeighbor(getValue(index)); while(w != -1){ if(!visit[w]){ cout< "; visit[w] = true; q.push(w); } w = getNextNeighbor(getValue(index), getValue(w)); } } delete []visit; } public: void MinSpanTree_Kruskal(); void MinSpanTree_Prim(const Type &v); public: void TopoLogicalSort(); protected: void DFS(const Type &v, bool *visit){ cout< "; int index = getVertexIndex(v); visit[index] = true; int w = getFirstNeighbor(v); while(w != -1){ if(!visit[w]){ DFS(getValue(w), visit); } w = getNextNeighbor(v, getValue(w)); } } private: Type *vertexList; //存放顶点的数组 int **edge; //存放边关系的矩阵 }; ////////////////////////////////////////////////////////////////////////////////////////////////////// typedef struct MstEdge{ int x; //row int y; //col int cost; }MstEdge; int cmp(const void *a, const void *b){ return (*(MstEdge*)a).cost - (*(MstEdge*)b).cost; } bool isSame(int *father, int i, int j){ while(father[i] != i){ i = father[i]; } while(father[j] != j){ j = father[j]; } return i == j; } void markSame(int *father, int i, int j){ while(father[i] != i){ i = father[i]; } while(father[j] != j){ j = father[j]; } father[j] = i; } template void GraphMtx ::MinSpanTree_Kruskal(){ int n = Graph ::getCurVertex(); //由于要用到父类的保护数据或方法,有模板的存在,必须加上作用域限定符; MstEdge *edge1 = new MstEdge[n*(n-1)/2]; int k = 0; for(int i = 0; i < n; i++){ for(int j = i+1; j < n; j++){ if(edge[i][j] != MAX_COST){ edge1[k].x = i; edge1[k].y = j; edge1[k].cost = edge[i][j]; k++; } } } qsort(edge1, k, sizeof(MstEdge), cmp); int *father = new int[n]; Type v1, v2; for(i = 0; i < n; i++){ father[i] = i; } for(i = 0; i < n; i++){ if(!isSame(father, edge1[i].x, edge1[i].y)){ v1 = getValue(edge1[i].x); v2 = getValue(edge1[i].y); printf("%c-->%c : %d\n", v1, v2, edge1[i].cost); markSame(father, edge1[i].x, edge1[i].y); } } } template void GraphMtx ::MinSpanTree_Prim(const Type &v){ int n = Graph ::getCurVertex(); int *lowCost = new int[n]; int *mst = new int[n]; int k = getVertexIndex(v); for(int i = 0; i < n; i++){ if(i != k){ lowCost[i] = edge[k][i]; mst[i] = k; }else{ lowCost[i] = 0; } } int min; int minIndex; int begin; int end; for(i = 0; i < n-1; i++){ min = MAX_COST; minIndex = -1; for(int j = 0; j < n; j++){ if(lowCost[j] != 0 && lowCost[j] < min){ min = lowCost[j]; minIndex = j; } } begin = mst[minIndex]; end = minIndex; printf("%c-->%c : %d\n", getValue(begin), getValue(end), min); lowCost[minIndex] = 0; int cost; for(j = 0; j < n; j++){ cost = edge[minIndex][j]; if(cost < lowCost[j]){ lowCost[j] = cost; mst[j] = minIndex; } } } } template void GraphMtx ::TopoLogicalSort(){ //拓扑排序 int n = Graph ::getCurVertex(); int *count = new int[n]; for(int i = 0; i < n; i++){ //count数组记载入度 count[i] = 0; } for(i = 0; i < n; i++){ for(int j = 0; j < n; j++){ if(edge[i][j] == 1){ count[j]++; //计算每个顶点的入度 } } } int top = -1; for(i = 0; i < n; i++){ if(count[i] == 0){ //模拟入栈push() count[i] = top; top = i; } } int v, w; for(i = 0; i < n; i++){ if(top == -1){ //有环图,直接返回; return; }else{ v = top; //模拟出栈pop() top = count[top]; printf("%c-->", getValue(v)); w = getFirstNeighbor(getValue(v)); while(w != -1){ if(--count[w] == 0){ count[w] = top; //删除了一个顶点,统计一遍,满足入栈push() top = w; } w = getNextNeighbor(getValue(v), getValue(w)); } } } cout<<"Over."< (2)、测试代码
#include"Graph1.h" int main(void){ GraphMtxgm; gm.insertVertex('A'); //0 gm.insertVertex('B'); //1 gm.insertVertex('C'); //2 gm.insertVertex('D'); //3 gm.insertVertex('E'); //4 gm.insertVertex('F'); //5 gm.insertEdge('A','B',1); gm.insertEdge('A','C',1); gm.insertEdge('A','D',1); gm.insertEdge('C','B',1); gm.insertEdge('C','E',1); gm.insertEdge('D','E',1); gm.insertEdge('F','D',1); gm.insertEdge('F','E',1); gm.showGraph(); // gm.MinSpanTree_Kruskal(); // cout<<"---------------------------------------------------------"< (3)、测试结果
测试图模型: