1, 遗传算法计算流程

pandaAlgorithm/FirstOptScheduling.cpp

@@ -109,5 +109,5 @@ double FirstOptScheduling::objectiveFunction(float cost, const map<string, doubl
 		}			
 	}
 
-	return 1 / (C1 + cost) * (1 + sum);
+	return 1 / (C1 + cost) * (1 + (double)sum);
 }
\ No newline at end of file

pandaAlgorithm/GenAlg.cpp

@@ -253,20 +253,43 @@ double GenAlg::averageFitness()
     return mAverageFitness;
 }
 
-void GenAlg::fitnessfunction(map<string, double>& monitorValues)
+double  GenAlg::fitnessfunction(float cost, map<string, double>& monitorValues)
 {
     // 计算适应
-    double objVal = mOptScheduling->objectiveFunction();
+    double objVal = mOptScheduling->objectiveFunction(cost, monitorValues);
+    return objVal;
 }
 
 void GenAlg::encoding(map<string, int>& phenotype, vector<char>& chromo)
 {
+    map<string, int>::iterator iter = phenotype.begin();
+    for (; iter != phenotype.end(); iter++)
+    {
 
+    }
 }
 
-void GenAlg::decoding(vector<char>& chromo, map<string, int>& phenotype)
+void GenAlg::decoding(vector<map<string, int>>& phenotype)
 {
+    size_t total = vecPop.size();
     
+    for (int i = 0; i < total; i++)
+    {
+        Genome genome = vecPop[i];
+        vector<char> genVec = genome.mBinaryGenVec;
+        for (int j = 0; j < genVec.size(); j++)
+        {
+            phenotype[i].insert(pair<string, char>(mPumpBits[j], genVec[j]));
+        }     
+    }
+}
+
+void GenAlg::decodingSingle(vector<char>& chromo, map<string, int>& phenotype)
+{
+    for (int j = 0; j < chromo.size(); j++)
+    {
+        phenotype.insert(pair<string, char>(mPumpBits[j], chromo[j]));
+    }
 }
 
 void GenAlg::setMaxMonitorVals(const  map<string, double>& maxMonitors)
@@ -278,3 +301,8 @@ void GenAlg::setMinMonitorsVals(const map<string, double>& minMonitors)
 {
     mOptScheduling->setMinMonitorsVals(minMonitors);
 }
+
+void GenAlg::setPumpBit(const vector<string>& pumpBit)
+{
+    mPumpBits = pumpBit;
+}
\ No newline at end of file

pandaAlgorithm/GenAlg.h

@@ -64,7 +64,7 @@ public:
     void select();
 
     // 根据监测点计算值，计算个体自适应度
-    void fitnessfunction(map<string,double>& monitorValues);
+    double fitnessfunction(float cost,map<string,double>& monitorValues);
 
     /**
     * @brief 编码, 将水泵开关状态编码成二进制状态：0表示管，1表示开
@@ -76,12 +76,16 @@ public:
     * @brief 解码, 将二进制状态吗解码成水泵对应的状态
     * @param 
     */
-    void decoding(vector<char>& chromo,map<string,int>& phenotype);
+    void decoding(vector<map<string, int>>& phenotype);
+
+    void decodingSingle(vector<char>& chromo, map<string, int>& phenotype);
 
     void setMaxMonitorVals(const  map<string, double>& maxMonitors);
 
     void setMinMonitorsVals(const map<string, double>& minMonitors);
 
+    void setPumpBit(const vector<string>& pumpBit);
+
 private:
     // 产生[a,b)之间的浮点数
     double random(int a=0, int b= RAND_MAX);
@@ -135,6 +139,9 @@ private:
     // 右边界
     double mRightPoint;
 
+    // 水泵状态位
+    vector<string> mPumpBits;
+
     // 优化调度函数
     std::unique_ptr<OptScheduling> mOptScheduling;
 };

pandaAlgorithm/GenEngine.cpp

-#include "GenEngine.h"
-
-GenEngine::GenEngine()
-{
-
-}
\ No newline at end of file

pandaAlgorithm/GenEngine.h

-#pragma once
-
-/**
-    ¿Í»§¶Ë
-*/
-class GenEngine
-{
-public:
-	explicit GenEngine();
-
-private:
-
-};

pandaAlgorithm/Genome.h

 #pragma once
 #include <vector>
 
+class CivOptSchedEngine;
+class GenAlg;
 /**
     染色体，实值编码
 */
@@ -8,7 +10,7 @@ class Genome
 {
 public:
     friend class GenAlg;
-    friend class GenEngine;
+    friend class CivOptSchedEngine;
 
     Genome() :fitness(0) {}
     Genome(std::vector <double> vec, double f) : vecGenome(vec), fitness(f) {}  //类的带参数初始化参数。  

pandaAlgorithm/pandaAlgorithm.vcxproj

@@ -153,7 +153,6 @@ copy OptScheduling.h $(OutDir)..\include  /y</Command>
   <ItemGroup>
     <ClInclude Include="FirstOptScheduling.h" />
     <ClInclude Include="GenAlg.h" />
-    <ClInclude Include="GenEngine.h" />
     <ClInclude Include="Genome.h" />
     <ClInclude Include="OptScheduling.h" />
     <ClInclude Include="pandaAlgorithm.h" />
@@ -162,7 +161,6 @@ copy OptScheduling.h $(OutDir)..\include  /y</Command>
   <ItemGroup>
     <ClCompile Include="FirstOptScheduling.cpp" />
     <ClCompile Include="GenAlg.cpp" />
-    <ClCompile Include="GenEngine.cpp" />
     <ClCompile Include="OptScheduling.cpp" />
   </ItemGroup>
   <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />

pandaAlgorithm/pandaAlgorithm.vcxproj.filters

@@ -27,9 +27,6 @@
     <ClInclude Include="GenAlg.h">
       <Filter>头文件</Filter>
     </ClInclude>
-    <ClInclude Include="GenEngine.h">
-      <Filter>头文件</Filter>
-    </ClInclude>
     <ClInclude Include="Genome.h">
       <Filter>头文件</Filter>
     </ClInclude>
@@ -47,8 +44,5 @@
     <ClCompile Include="GenAlg.cpp">
       <Filter>源文件</Filter>
     </ClCompile>
-    <ClCompile Include="GenEngine.cpp">
-      <Filter>源文件</Filter>
-    </ClCompile>
   </ItemGroup>
 </Project>
\ No newline at end of file

pandaAnalysis/CivOptSchedEngine.cpp

@@ -2,12 +2,16 @@
 #include "CivInpConvertor.h"
 #include "GenAlg.h"
 #include "FirstOptScheduling.h"
+#include "CivPumpHelper.h"
+#include "CivSchedulingCompute.h"
+#include "Genome.h"
 
 
 
 CivOptSchedEngine::CivOptSchedEngine(const string& uri):mUri(uri)
 {
-
+	mMutRate = 0.45;
+	mCrossRate = 0.07;
 }
 
 bool CivOptSchedEngine::optimalScheduling()
@@ -16,19 +20,126 @@ bool CivOptSchedEngine::optimalScheduling()
 	CivInpConvertor convertor(mUri);
 	string inpFile = convertor.convertBaseInp();
 
-	// 
+	// 获取水泵个数,根据水泵个数确定基因编码长度
+	CivPumpHelper pumpHelper(mUri);
+	mGenLength = pumpHelper.getPumpNumbers();
+
+	// 获取本点号和code的映射
+	map<string, string> snToCodeMap;
+	pumpHelper.getMap("本点号", "code", snToCodeMap);
+
+	// 获取本点号集合
+	vector<string> snVec;
+	pumpHelper.getPumpSn(snVec);
+
+	// 开始遗传算法
 	GenAlg genAlg(GenAlg::BinaryCoding);
 
+	// 设置水泵的编码位
+	genAlg.setPumpBit(snVec);
+
 	// 种群初始化
 	popsize = 100;
 	genAlg.init(popsize, mMutRate, mCrossRate, mGenLength, 0, 0);
-	// genAlg.epoch();
 	
+	// 构造水力计算对象
+	CivSchedulingCompute schedulingCompute;
+	vector<string> monitorVec;
+	for (auto iter = mMonitoring.begin(); iter != mMonitoring.end(); iter++)
+	{
+		monitorVec.push_back(iter->first);
+	}
+	schedulingCompute.setMonitors(monitorVec);
+	schedulingCompute.openFile(inpFile);
+
+	// 原始管网计算一次水力，保留调度前的水力计算结果
+	if (!schedulingCompute.calculate())
+		return false;
+
+	// 保存原始管网监测点的模拟值
+	schedulingCompute.getMonitorsValue(mBforeSchedulingResults);
+
+	// 开始迭代计算
+	int index = 0;
+	while (index++ < popsize)
+	{
+		// 管网平差计算
+		vector<map<string, int>>monitorsMap;
+		genAlg.decoding(monitorsMap);
+
+		// 计算个体自适度
+
+		// 根据个体自适应度进行选择
+
+		// 自适应交叉变异
+
+		// 产生下一代种群
+	}
+
+	// 获取最好的
+	Genome genome = genAlg.bestFitness();
+	vector<char> genVec = genome.mBinaryGenVec;
+
+	// 最优水泵组合
+	genAlg.decodingSingle(genVec, mPumpBestStatus);
+
+	// 再做一次水力计算，计算调度后的值
+	schedulingCompute.updatePumpStatus(mPumpBestStatus);
+	schedulingCompute.calculate();
+
+	// 最有调度值
+	schedulingCompute.getMonitorsValue(mBforeSchedulingResults);
+
+	// 结束计算
+	schedulingCompute.close();
+	return true;
 }
 
 void CivOptSchedEngine::schedulingResultToJson(string& json)
 {
+	// 水泵:组合
+	json.append("{\"水泵状态\":{");
+
+	map<string, int>::iterator iter = mPumpBestStatus.begin();
+	for (;iter!=mPumpBestStatus.end();iter++)
+	{
+		json.append(iter->first + ":" + to_string(iter->second));
+		json.append(",");
+	}
+	json = json.substr(0, json.length() - 1);
+	json.append("},");
+
+	// 调度组合
+	json.append("\"监测点:[\"");
+	int total = mBforeSchedulingResults.size();
+	for (int i = 0; i < total; i++)
+	{
+		map<string, double> beforeResult = mBforeSchedulingResults[i];
+		map<string, double> afterResult = mAfterSchedulingResults[i];
+
+		json.append("{");
+		for (auto iter = beforeResult.begin(); iter != beforeResult.end(); iter++)
+		{
+			string monitorName = iter->first;
+			double beforeMonitorVal = iter->second;
+
+			auto afteriter = afterResult.find(monitorName);
+			if (afteriter == afterResult.end())
+				continue;
+
+			double afterMonitorvVal = afteriter->second;
 
+			json.append("\""+monitorName+"\":[");
+			json.append(to_string(beforeMonitorVal));
+			json.append(",");
+			json.append(to_string(afterMonitorvVal));
+			json.append("],");
+		}
+		json = json.substr(0, json.length() - 1);
+		json.append("},");
+	}
+	json.substr(0, json.length() - 1);
+	json.append("]}");
 }
 
 void CivOptSchedEngine::setMonitor(const map<string, vector<double>>& monitorMap)

pandaAnalysis/CivOptSchedEngine.h

@@ -38,11 +38,13 @@ private:
 	// 编码与状态的映射
 	map<int, string> mStatusBit;
 
-	// 调度结果
-	vector<map<string, int>> mSchedulingResults;
+	// 选出的最优组合
+	map<string, int> mPumpBestStatus;
 
 	// 监测点
 	map<string, vector<double>> mMonitoring;
+	vector<map<string, double>> mBforeSchedulingResults;
+	vector<map<string, double>> mAfterSchedulingResults;
 
 	// 数据连接地址
 	string mUri;

pandaAnalysis/CivReportReader.cpp

@@ -14,14 +14,14 @@ void CivReportReader::readEnergy(const string& pumpSn, string& enery)
 
 bool CivReportReader::open(const string& reportFile)
 {
-	ifstream stream(reportFile.c_str());
+	ifstream reader(reportFile.c_str());
 
 	// жȡ
 	string sLine;
-	while (getline(stream, sLine))
+	while (getline(reader, sLine))
 	{
 		
 	}
 
-	stream.close();
+	reader.close();
 }

pandaAnalysis/CivSchedulingCompute.cpp

@@ -103,7 +103,7 @@ void CivSchedulingCompute::close()
     ENclose();
 }
 
-void CivSchedulingCompute::updatePumpStatus(const map<string, char>& pumpStatus)
+void CivSchedulingCompute::updatePumpStatus(const map<string, int>& pumpStatus)
 {
     mPumpStatus.clear();
     mPumpStatus = pumpStatus;

pandaAnalysis/CivSchedulingCompute.h

@@ -3,7 +3,6 @@
 #include <string>
 
 using namespace std;
-
 /**
      优化调度计算类
 */
@@ -25,7 +24,7 @@ public:
 	void close();
 
 	// 更新水泵开关状态
-	void updatePumpStatus(const map<string, char>& pumpStatus);
+	void updatePumpStatus(const map<string, int>& pumpStatus);
 
 	// 获取监测点计算出的值
 	void getMonitorsValue(vector<map<string, double>>& monitorMap);
@@ -45,7 +44,7 @@ private:
 	int  mErrcode = 0;
 
 	// 更新水泵的状态
-	map<string, char> mPumpStatus;
+	map<string, int> mPumpStatus;
 
 	// 存储测点的计算值
 	vector<map<string, double>> mMonitorsValue;

pandaDbManager/CivPumpHelper.cpp

@@ -33,3 +33,45 @@ void CivPumpHelper::getMap(const string& key, const string& val, map<string, str
 		res.insert(pair<string, string>(keyVal, valVal));
 	}
 }
+
+int CivPumpHelper::getPumpNumbers()
+{
+	string sql = "select count(id) as cunt from " + mTable;
+	if (!mConn->execSql(sql))
+		return 0;
+
+	vector<map<string,string>> pumpRes;
+	if (!mConn->queryResult(pumpRes))
+		return 0;
+
+	if (pumpRes.size() <= 0)
+		return 0;
+
+	map<string, string> pumpMap = pumpRes[0];
+	map<string, string>::iterator iter = pumpMap.find("cunt");
+	if (iter == pumpMap.end())
+		return 0;
+
+	string pumpSize = iter->second;
+	int pumps = atoi(pumpSize.c_str());
+	return pumps;
+}
+
+void CivPumpHelper::getPumpSn(vector<string>& pumpNames)
+{
+	const string sz = "";
+	vector<map<string, string>> vecMap;
+	if (!mConn->query(mTable, { sz }, vecMap))
+		return;
+
+	if (vecMap.size() <= 0)
+		return;
+
+	size_t total = vecMap.size();
+	for (int i = 0; i < total; i++)
+	{
+		map<string, string> tempMap = vecMap[i];
+		string val = tempMap.find(sz)->second;
+		pumpNames.push_back(val);
+	}
+}

pandaDbManager/CivPumpHelper.h

 #pragma once
 #include<string>
 #include<map>
+#include<vector>
 
 #include "pandaDbManager.h"
 
@@ -20,6 +21,11 @@ public:
 	// 获取指定属性字段键值对映射
 	void getMap(const string& key, const string& val, map<string, string>& res);
 
+	// 获取水泵的个数
+	int getPumpNumbers();
+
+	// 获取水泵的编号
+	void getPumpSn(vector<string>& pumpNames);
 private:
 	CivConnection* mConn = nullptr;