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我们使用了模拟退火+spfa最大流最小费用算法，通过上百次迭代，获取近似解。
核心代码如下：
package com.cacheserverdeploy.deploy;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map.Entry;
import java.util.Queue;
import java.util.Random;
import java.util.Stack;
public class Deploy {
/**
* 你需要完成的入口 <功能详细描述>
*
* @param graphContent
* 用例信息文件
* @return [参数说明] 输出结果信息
* @see [类、类#方法、类#成员]
*/
protected static final int INT_MAX = 300000000;
// protected static final int INT_MAX = Integer.MAX_VALUE;
protected static int nodeNum;
protected static int n;
protected static int consumersNum;
protected static int linksNum_undirected;
protected static int linksNum_directed;
protected static int superTID;
protected static int superSID;
protected static Link[] links;
protected static ConsumerNode[] consumers;
protected static int serverCost;
protected static int totalLinksNum;
protected static Link[] linksSuper;
protected static int index;
protected static int requiredFlow = 0;
protected static int[] degree;// 存储所有的点的度
protected static int[] nodeIndexByDegree;// 按度大小存储链路节点的ID
protected static MinCMaxF mcmf;
protected static long startTime;
protected static long stopTime;
/******************************************/
public static String[] deployServer(String[] graphContent) {
/** do your work here **/
startTime = System.currentTimeMillis();
// 获取输入文件第一行信息
String[] lineOne = graphContent[0].split(" ");
n = Integer.parseInt(lineOne[0]);
nodeNum = n;
// new linksNum = Integer.parseInt(lineOne[1]);
linksNum_undirected = Integer.parseInt(lineOne[1]);
linksNum_directed = 2 * linksNum_undirected;
consumersNum = Integer.parseInt(lineOne[2]);
degree = new int[nodeNum];
nodeIndexByDegree = new int[nodeNum];
// 获取输入文件的第二行有效信息
String lineTwo = graphContent[2];
serverCost = Integer.parseInt(lineTwo);
/********************* 两倍链路 ***************************/
// 链路数组
totalLinksNum = linksNum_directed + 2 * consumersNum + nodeNum;
links = new Link[linksNum_directed];
Link tmpLink;
for (int i = 0; i < linksNum_undirected; i++) {
String[] strs = graphContent[i + 4].split(" ");
int from = Integer.parseInt(strs[0]);
int to = Integer.parseInt(strs[1]);
int capibility = Integer.parseInt(strs[2]);
int costPerUnit = Integer.parseInt(strs[3]);
tmpLink = new Link(from, to, capibility, costPerUnit, 0);
links[2 * i] = tmpLink;
tmpLink = new Link(to, from, capibility, costPerUnit, 0);
links[2 * i + 1] = tmpLink;
}
linksSuper = new Link[totalLinksNum];
for (int i = 0; i < linksNum_directed; i++)
linksSuper[i] = links[i];
index = linksNum_directed;
// 设置度数组
setDegreeArr(degree, nodeIndexByDegree, links);
/*******************************************************/
/****************************/
// for (int i : maximunFront)
// System.out.print(i + " ");
// 消费节点
consumers = new ConsumerNode[consumersNum];
ConsumerNode tmpNode;
for (int i = 0; i < consumersNum; i++) {
String[] strs = graphContent[i + 5 + linksNum_undirected]
.split(" ");
int cID = Integer.parseInt(strs[0]);
int neighborID = Integer.parseInt(strs[1]);
int requiredBand = Integer.parseInt(strs[2]);
tmpNode = new ConsumerNode(cID, neighborID, requiredBand);
requiredFlow += requiredBand;
consumers[i] = tmpNode;
}
// 定义两个超级节点:超级源点，超级汇聚节点
superSID = nodeNum;
superTID = nodeNum + 1;
n = n + 2;
// 将消费节点加入及相关链路加入网络
for (int i = 0; i < consumersNum; i++) {
// 将消费节点链接到原网路中
Link tmpConsumerLink = new Link(consumers[i].getNeighborID(), n,
consumers[i].getRequiredBand(), 0, 0);
linksSuper[index++] = tmpConsumerLink;
// 指向超级汇聚节点,消费节点ID用n+i表示，汇聚节点用n+consumersNum表示
Link tmpConsumerLink2 = new Link(n, superTID,
consumers[i].getRequiredBand(), 0, 0);
linksSuper[index++] = tmpConsumerLink2;
n++;
}
/**********************************************************************************/
// System.out.println("n after add server:"+n);
// 生成node数组
// Node[] nodes = new Node[nodeNum];
// for (int i = 0; i < nodeNum; i++) {
// nodes[i] = new Node(i, 0);
// }
// nodes[nodeNum] = new Node(nodeNum, 0);
// nodes[nodeNum + 1] = new Node(nodeNum + 1, 0);
// // 消费节点node
// for (int i = 0; i < consumersNum; i++) {
// nodes[i + nodeNum + 2] = new Node(i + nodeNum + 2, 0);
// }
// // 服务器节点
// for (int i = 0; i < nodeNum; i++) {
// nodes[i + nodeNum + 2 + consumersNum] = new Node(i + nodeNum + 2
// + consumersNum, serverCost);
// // nodes[i + nodeNum + 2 + consumersNum] = new Node(i + nodeNum + 2
// // + consumersNum, 0);
// }
/****************************************/
// 调用模拟退火
SA.getSA();
/***************** PathListWithFlow()方式返回数据 *****************/
List<String> pathesList = mcmf.getPathListWithFlow();
String[] strResult = new String[pathesList.size() + 2];
strResult[0] = pathesList.size() + "";
strResult[1] = "";
for (int i = 0; i < pathesList.size(); i++) {
strResult[i + 2] = "";
String[] str = pathesList.get(i).split(" ");
int consumer = Integer.parseInt(str[str.length - 3]) - nodeNum - 2;
int flow = Integer.parseInt(str[str.length - 1]);
for (int j = 1; j < str.length - 3; j++)
strResult[i + 2] = strResult[i + 2] + str[j] + " ";
strResult[i + 2] = strResult[i + 2] + consumer + " " + flow;
}
/**************************************************************/
// for (String i : strResult)
// System.out.println("strResult:" + i);
/**************************************************************/
return strResult;
}
/*
* 度处理
*/
private static void setDegreeArr(int[] degree, int[] nodeIndexByDegree,
Link[] links) {
for (int i : degree) {
i = 0;
}
for (Link i : links) {
degree[i.getlStartID()]++;
degree[i.getlEndID()]++;
}
/***********************/
System.out.print("degree:");
for (int i : degree) {
System.out.print(i + " ");
}
System.out.println();
int[] degreeCopy = new int[degree.length];
int index = 0;
for (int i : degree) {
degreeCopy[index++] = i;
}
for (int i = 0; i < nodeIndexByDegree.length; i++) {
int maxIndex = 0;
for (int j = 0; j < degreeCopy.length; j++) {
if (degreeCopy[j] > degreeCopy[maxIndex]) {
maxIndex = j;
}
}
nodeIndexByDegree[i] = maxIndex;
degreeCopy[maxIndex] = -1;
}
/***********************/
System.out.print("sort by degree:");
for (int i : nodeIndexByDegree) {
System.out.print(i + " ");
}
System.out.println();
}
/*
* 插入服务器
*/
public static void insertServerLink(Link[] linksSuper, int[] target) {
/********************** 单倍链路 ***********************/
// index = linksNum_undirected + 2 * consumersNum;
/********************** 双倍链路 ***********************/
index = linksNum_directed + 2 * consumersNum;
for (int i = 0; i < nodeNum; i++) {
Link tmpServerLink = new Link(superSID, i, target[i], 0, 0);
linksSuper[index++] = tmpServerLink;
}
}
}
/*
* 最小费用最大流
*/
class MinCMaxF {
private final int INT_MAX = 300000000;
// private final int INT_MAX = Integer.MAX_VALUE;;
private int flow = 0;
private int cost = 0;
private int N;// 点的个数
private int E;// 边的个数
protected static Link[] linksDouble;
private Link[] links;
protected static List<Integer>[] G;
private boolean[] isInQueue;// 判断一个点是否在队列当中
// private Node[] nodes;
private List<Integer> costList = new ArrayList<Integer>();// 存储所有的最大刘路径上的cost集合
private List<Integer> flowList = new ArrayList<Integer>();// 每条路径上的flow
private boolean[] isScaned;
private int lastServerLinkID;
private int[] d;// 起点到d[i]的最短路径保存值
private int[] p;// 用来记录路径，保存是上一条弧
private int[] a;// 增广路径后的改进量
private boolean[] isServer;// 第i个节点否为服务器
private int s;
private int t;
// DFS输出路径与计算cost
private static List<String> pathListWithFlow = new ArrayList<String>();
private int miniFlow = INT_MAX;
public MinCMaxF(Link[] links, int n, int s, int t) {
super();
this.links = links;
this.E = links.length;// 初始化边的个数
this.N = n;// 节点个数
this.isScaned = new boolean[this.N];
this.s = s;
this.t = t;
init();// 将边添加进邻接表
minCostMaxFlow(s, t);
/*********************************/
// System.out.println("mincost:" + minCostMaxFlow(s, t));
// for (String l : pathesList) {
//
// System.out.println("path:" + l);
// }
/********************** 各链路占用的带宽 *************************/
// ArrayList<Integer> eachLinkInPath = new ArrayList<Integer>(0);
// LinkedHashMap<String, Integer> hashMap = new LinkedHashMap<String,
// Integer>();
// for (int i = 0; i < pathesList.size(); i++) {
// int bandCost = flowList.get(i);
// String[] strArray = pathesList.get(i).split(" ");
// String[] pathArr = new String[strArray.length - 2];
// for (int j = 0; j < pathArr.length - 1; j++) {
// pathArr[j] = strArray[j + 1];
// }
// pathArr[pathArr.length - 1] = Integer
// .parseInt(strArray[strArray.length - 2])
// - Deploy.nodeNum
// - 2 + "";
// for (int j = 0; j < pathArr.length - 1; j++) {
// if (hashMap.get(pathArr[j] + " " + pathArr[j + 1]) == null) {
// hashMap.put(pathArr[j] + " " + pathArr[j + 1], bandCost);
// } else {
// int sum = hashMap.get(pathArr[j] + " " + pathArr[j + 1])
// + bandCost;
// hashMap.put(pathArr[j] + " " + pathArr[j + 1], sum);
// }
// }
//
// }
// System.out.print("====================输出链路与对应的i占用的带宽");
// for (Entry<String, Integer> entry : hashMap.entrySet()) {
// System.out.println(entry.getKey() + " " + entry.getValue());
// }
/**********************************************************/
//
// for(int c : costList){
// System.out.println("cost:"+c);
// }
//
// for (int c : flowList) {
// System.out.println("flow:" + c);
// }
/************** 输出各个节点做接收到的流量之和 ****************/
// int[] flowSumEachConsumer = new int[Deploy.consumersNum];
// for (int i : flowSumEachConsumer)
// i = 0;
// int indexTmp = 0;
// for (String l : pathesList) {
// /*******************************/
// // System.out.println("path:" + l);
// String[] strArr = l.split(" ");
// int consumerID = Integer.parseInt(strArr[strArr.length - 2])
// - Deploy.nodeNum - 2;
// flowSumEachConsumer[consumerID] += flowList.get(indexTmp);
// indexTmp++;
// }
// for (int i = 0; i < flowSumEachConsumer.length; i++)
// System.out.println(i + " flowSum:" + flowSumEachConsumer[i]);
/********************************************************/
// System.out.println("flow:" + flow);
// System.out.println("required flow:" + Deploy.requiredFlow);
// 如果输出的流量不符合u要求,说明是算法失败
if (flow != Deploy.requiredFlow)
cost = INT_MAX;
// System.out.println("cost:" + cost);
}
private void init() {
this.linksDouble = new Link[this.E * 2];
this.G = new ArrayList[this.N];
this.isInQueue = new boolean[this.N];
for (int i = 0; i < this.N; i++) {
this.G[i] = new ArrayList<Integer>();
this.isInQueue[i] = false;
isScaned[i] = false;
this.lastServerLinkID = -1;
}
this.d = new int[this.N];
this.p = new int[this.N];
this.a = new int[this.N];
this.isServer = new boolean[this.N];
for (boolean i : this.isServer)
i = false;
// 将所有的边添加进来
for (int i = 0; i < E; i++) {
int from = this.links[i].getlStartID();
int to = this.links[i].getlEndID();
int cap = this.links[i].getlBand();
int flow = this.links[i].getFlow();
int cost = this.links[i].getlBCostPerUnit();
this.linksDouble[2 * i] = new Link(from, to, cap, cost, 0);
this.linksDouble[2 * i + 1] = new Link(to, from, 0, -cost, 0);
// 按照边的标号存储邻接信息
this.G[from].add(2 * i);
this.G[to].add(2 * i + 1);
}
}
/*
* 循环执行SPFA算法，直到SPFA算法返回值是false
*/
private void minCostMaxFlow(int s, int t) {
while (SPFA(s, t))
;
// cost
for (int i = 0; i < this.N; i++) {
if (isServer[i])
cost += Deploy.serverCost;
}
}
/*
* SPFA算法求解最大流最小费用流
*/
private boolean SPFA(int s, int t) {
for (int i = 0; i < this.N; i++) {
d[i] = INT_MAX;
this.isInQueue[i] = false;
}
d[s] = 0;
isInQueue[s] = true;
p[s] = 0;
a[s] = INT_MAX;
Queue<Integer> q = new LinkedList<Integer>();
q.offer(s);
while (!q.isEmpty()) {
int u = (int) q.peek();
q.poll();
isInQueue[u] = false;
for (int i = 0; i < G[u].size(); i++) {
Link l = linksDouble[(int) G[u].get(i)];
if (l.getlBand() > l.getFlow()
&& d[l.getlEndID()] > d[u] + l.getlBCostPerUnit()) {// 满足增广要求
d[l.getlEndID()] = d[u] + l.getlBCostPerUnit();
p[l.getlEndID()] = (int) G[u].get(i);
a[l.getlEndID()] = (a[u] < (l.getlBand() - l.getFlow()) ? a[u]
: (l.getlBand() - l.getFlow()));
if (!isInQueue[l.getlEndID()]) {
isInQueue[l.getlEndID()] = true;
q.offer(l.getlEndID());
}
}
}
}
if (Math.abs(d[t] - INT_MAX) < 100000) {
return false;
}
int u = t;
/**************************************/
int front = 0;
while (u != s) {
// 更新正向边与反向边
linksDouble[p[u]].setFlow(linksDouble[p[u]].getFlow() + a[t]);
linksDouble[p[u] ^ 1].setFlow(linksDouble[p[u] ^ 1].getFlow()
- a[t]);
/****************************************/
front = u;
u = linksDouble[p[u]].getlStartID();
}
/**********************************************************/
if (!this.isServer[front]) {
this.isServer[front] = true;
}
cost = cost + d[t] * a[t];
flow = flow + a[t];
this.costList.add(d[t] * a[t]);
this.flowList.add(a[t]);
return true;
}
/*
* findPath算法
*/
protected static boolean findPath() {
Stack<Integer> pathStack = new Stack<Integer>();
Stack<Integer> nodeStack = new Stack<Integer>();
nodeStack.push(Deploy.superSID);
int u = Deploy.superSID;
int mFlow = Deploy.INT_MAX;
int front = u;
// 寻找一条从源点到汇点的路径
while (u != Deploy.superTID) {
for (int i = 0; i < G[u].size(); i++) {
int linkNum = G[u].get(i);
Link l = linksDouble[linkNum];
if (l.getFlow() <= 0)// 不要考虑负权重的边
continue;
if (l.getFlow() > 0) {// 链路上仍然有流量
mFlow = mFlow < l.getFlow() ? mFlow : l.getFlow();
u = l.getlEndID();
nodeStack.push(u);
pathStack.push(linkNum);
break;
}
}
if (u == front)
return false;
}
/************************************/
// 在路径中的每条边上都删除一个mFlow
while (!pathStack.isEmpty()) {
int linkNum = pathStack.pop();
linksDouble[linkNum]
.setFlow(linksDouble[linkNum].getFlow() - mFlow);
}
String tmpPath = "";
while (!nodeStack.isEmpty()) {
tmpPath = nodeStack.pop() + " " + tmpPath;
}
tmpPath = tmpPath + mFlow;
pathListWithFlow.add(tmpPath);
return true;
}
public List<Integer> getFlowList() {
return flowList;
}
public int getCost() {
return cost;
}
public List<String> getPathListWithFlow() {
return pathListWithFlow;
}
}
/*
* 实现模拟退火算法
*/
class SA {
private static final int INT_MAX = 300000000;
// private static final int T = 1000;// 初始化温度
private static int T;// 初始化温度
private static final double Tmin = 1e-8;// 温度的下界
private static final int K = 100;// 迭代的次数
private static final double delta = 0.98;// 温度的下降率
private static int[] serverInsert = new int[Deploy.nodeNum];
private static boolean[] hasBeenDeleted = new boolean[Deploy.nodeNum];
private static boolean[] hasBeenAdded = new boolean[Deploy.nodeNum];
/*
*
*/
public static void getSA() {
if(Deploy.nodeNum < 600){
T = 1000;
}else{
T = Deploy.consumersNum * Deploy.serverCost;
}
int costBest;
int isSamedCounter = 0;// 计数目前已经有多少次的结果是相同的
// 初始的服务器状态,全部直连消费节点的邻节点
for (int i = 0; i < Deploy.consumersNum; i++)
serverInsert[Deploy.consumers[i].getNeighborID()] = INT_MAX;
// 保存上一次的服务器部署方案
int[] backUp = Arrays.copyOf(serverInsert, Deploy.nodeNum);
// 保存最优的服务器部署方案
int[] bestDeploy = Arrays.copyOf(serverInsert, Deploy.nodeNum);
// 执行SPFA
for (int i = 0; i < Deploy.nodeNum; i++)
Deploy.insertServerLink(Deploy.linksSuper, serverInsert);
Deploy.mcmf = new MinCMaxF(Deploy.linksSuper, Deploy.n,
Deploy.superSID, Deploy.superTID);
// 得到最优解的初始解
costBest = Deploy.mcmf.getCost();
/**************************************************/
System.out.println("costBest:" + costBest);
isSamedCounter = 0;
int costLast = costBest;
int costTmp;
// 随机类
Random random = new Random();
// 迭代过程
// 迭代到找到最优或到时间为止
// 溫度变量
double t = T;
while (t > Tmin) {
//内部迭代
for (int i = 0; i < K; i++) {
Deploy.stopTime = System.currentTimeMillis();
//时间到了,就停止迭代
if (Deploy.stopTime - Deploy.startTime >= 86000){
break;
}
//删除服务器中可删除的度最小的
boolean deleteSuccess = deleteMinium();
boolean addSuccess;
//删除成功
if(deleteSuccess){
costTmp = Deploy.mcmf.getCost();
if(costTmp == INT_MAX){
serverInsert = Arrays.copyOf(backUp, Deploy.nodeNum);
// continue;
}
}else{
hasBeenDeleted = new boolean[Deploy.nodeNum];
}
if(!deleteSuccess){
// deleteSuccess = deleteMinium();
//如果删除读最小的服务器节点失败,则添加度最大的点做服务器
addSuccess = addMaximum();
if(addSuccess){
costTmp = Deploy.mcmf.getCost();
if(costTmp == INT_MAX){
serverInsert = Arrays.copyOf(backUp, Deploy.nodeNum);
// continue;
}
}
if(! addSuccess){
//如果添加度最大的点任然失败,则恢复访问控制hasBeenProcessed
hasBeenAdded = new boolean[Deploy.nodeNum];
// continue;
}
}
/*************************************************/
/**********************测试************************/
//
// for (int j = 0; j < Deploy.nodeNum; j++){
// if(serverInsert[j] == INT_MAX)
// System.out.print(j+"\t");
// else{
// System.out.print(0+"\t");
// }
// }
// System.out.println();
/*************************************************/
costTmp = Deploy.mcmf.getCost();
/*************************************/
// System.out.println("costTmp:" + costTmp);
// System.out.println("costLast:" + costLast);
// System.out.println("costBest:" + costBest);
if (costTmp < costLast) {
backUp = Arrays.copyOf(serverInsert, Deploy.nodeNum);
costLast = costTmp;
} else {
if (1 / (1 + Math.exp(-(costTmp - costLast) / T)) > random
.nextDouble()) {
// backUp = Arrays.copyOf(serverInsert, Deploy.nodeNum);
// costLast = costTmp;
} else {
serverInsert = Arrays.copyOf(backUp, Deploy.nodeNum);
}
}
}
System.out.println("costBest:" + costBest);
if (costLast < costBest) {
// backUp = Arrays.copyOf(serverInsert, Deploy.nodeNum);
bestDeploy = Arrays.copyOf(backUp, Deploy.nodeNum);
costBest = costLast;
isSamedCounter = 0;
}else{
isSamedCounter++;
}
if (isSamedCounter > 100) {
break;
}
if (Deploy.stopTime - Deploy.startTime >= 86000){
break;
}
// 温度下降
t *= delta;
}
// 执行最优方案
serverInsert = Arrays.copyOf(bestDeploy, Deploy.nodeNum);
for (int i = 0; i < Deploy.nodeNum; i++)
Deploy.insertServerLink(Deploy.linksSuper, serverInsert);
Deploy.mcmf = new MinCMaxF(Deploy.linksSuper, Deploy.n,
Deploy.superSID, Deploy.superTID);
/***************** 寻路,输出路径 ***********************/
while (MinCMaxF.findPath())
;
}
/*
* @para
*/
private static boolean deleteMinium() {
// 删除已有服务器中度最小的那个
/********************************************************/
// Long time1 = System.currentTimeMillis();
for (int i = Deploy.nodeNum - 1; i >= 0; i--) {
if (serverInsert[Deploy.nodeIndexByDegree[i]] == INT_MAX
&& !hasBeenDeleted[Deploy.nodeIndexByDegree[i]]) {//
serverInsert[Deploy.nodeIndexByDegree[i]] = 0;
hasBeenDeleted[Deploy.nodeIndexByDegree[i]] = true;
/*****************************************************/
// System.out.println("删除最小点:" + Deploy.nodeIndexByDegree[i]);
// SPFA
for (int j = 0; j < Deploy.nodeNum; j++)
Deploy.insertServerLink(Deploy.linksSuper, serverInsert);
Deploy.mcmf = new MinCMaxF(Deploy.linksSuper, Deploy.n,
Deploy.superSID, Deploy.superTID);
/********************************************************/
// Long time2 = System.currentTimeMillis();
// System.out.println("****************time2-time1:" + (time2 - time1));
return true;
}
}
return false;
}
private static boolean addMaximum() {
// 从剩余链路节点中选择一个度最大的节点作为服务器节点
/********************************************************/
// Long time1 = System.currentTimeMillis();
for (int i = 0; i < Deploy.nodeNum; i++) {
if (serverInsert[Deploy.nodeIndexByDegree[i]] == 0
&& !hasBeenAdded[Deploy.nodeIndexByDegree[i]]) {
serverInsert[Deploy.nodeIndexByDegree[i]] = INT_MAX;
hasBeenAdded[Deploy.nodeIndexByDegree[i]] = true;
/*****************************************************/
// System.out.println("添加最大点:" + Deploy.nodeIndexByDegree[i]);
// SPFA
for (int j = 0; j < Deploy.nodeNum; j++)
Deploy.insertServerLink(Deploy.linksSuper, serverInsert);
Deploy.mcmf = new MinCMaxF(Deploy.linksSuper, Deploy.n,
Deploy.superSID, Deploy.superTID);
/********************************************************/
// Long time2 = System.currentTimeMillis();
// System.out.println("****************time2-time1:" + (time2 - time1));
return true;
}
}
return false;
}
/*
*
*/
private static void setRandom(int min, int max, int n, HashSet<Integer> set) {
Random random = new Random();
for (int i = 0; i < n; i++) {
int ranInt = random.nextInt(max - min) + min;
if (!set.add(ranInt)) {
i--;
}
}
}
}
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