水库调度程序代码（遗传算法）

package GA; /** * <p>Title: </p> * <p>Description: </p> * <p>Copyright: Copyright (c) 2012</p> * <p>Company: </p> * @author not attributable * @version 1.0 */ import java.text.DecimalFormat; import java.util.Arrays; import java.util.HashMap; import java.util.Random; public class Modified_GA_ertan { //程序入口 public static void main(String[] args) { Modified_GA_ertan key = new Modified_GA_ertan(); key.init(); key.Operation(); } double Low_v = 24.2; double Gao_v = 57.9; double N_Maxzhji = 330; // 装机容量，单位万kW double N_Minzhji = 98; // 保证出力，单位万kW double N_MaxQ = 2400; // 发电机组最大应用流量 double A = 8.6; // 出力系数 double N = 0.1; // 精度_得到337个区间，338个点 double a = 1000000; // 调整惩罚的参数 double b = 0.5; // 调整惩罚的参数 int M = 200; // 初始种群规模 int T = 300; // 进化代数 double Ps = 0.8; // 选择概率 double Pc = 0.9; // 交叉概率 double Pm = 0.05; // 变异概率 int Range = 6; // 变异范围 int Longer = 12; double[] optimal_H = new double[Longer + 1]; // 存放最优水位过程 double[] optimal_N = new double[Longer]; // 存放最优出力过程 double[] optimal_E = new double[T]; // 存放每次进化的最优适应值(解码) double[] optimal_N_Q = new double[Longer]; // 存放最优发电引用流量过程 double[] loss_Q = new double[Longer]; // 存放最优弃水过程 double[] optimal_chuku_Q = new double[Longer]; // 存放最优出库水量过程 // 入库流量 double[] q_in = new double[] { 1309, 2476, 4299, 3761, 2071, 1127, 713, 529, 466, 465, 555, 670}; // 二滩水库水位——库容关系 double[] ia = new double[] { 1155, 1156, 1158, 1160, 1162, 1164, 1166, 1168, 1170, 1172, 1174, 1176, 1178, 1180, 1182, 1184, 1186, 1188, 1190, 1192, 1194, 1196, 1198, 1200}; double[] iv = new double[] { 24.2, 24.52, 25.56, 26.61, 27.9, 29.2, 30.5, 31.8, 33.1, 34.5, 35.9, 37.3, 38.7, 40.11, 41.78, 43.45, 45.12, 46.8, 48.5, 50.2, 52, 53.9, 55.9, 57.93}; // 二滩水库泄流量——下游水库关系 double[] ib = new double[] { 1009.5, 1010.85, 1012.38, 1014.5, 1016.4, 1018.1, 1019.6, 1020.8, 1021.8, 1022.55, 1023.06, 1023.34, 1023.38}; double[] iq = new double[] { 0, 400, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000}; double[] V; // 存库容值 int m; // 库容离散数 double[] H_Cshuiwei; // 对应库容的水位（m+1）个 int[][] individual_Group_Old = new int[M][q_in.length + 1]; int[][] individual_Group_New = new int[M][q_in.length + 1]; public void init() { // 库容离散(从大到小) m = (int) ( (Gao_v - Low_v) / N); // 化为m等分,有m+1个点 double[] V = new double[ (m + 1)]; V[0] = Low_v; for (int i = 0; i < m + 1; i++) { V[i] = V[0] + i * (Gao_v - Low_v) / m; } this.V = V; // 产生初始种群 // 对应库容的水位（m+1）个 double[] H_Cshuiwei = new ChaZhi().ChaZhiShuiWei(V, ia, iv); this.H_Cshuiwei = H_Cshuiwei; Init_Group(); } public void Operation() { int t = 1; while (t <= T) { Evaluate_Group(t); Select(); GA_Cross(); GA_Mutation(); GA_Production(); t++; } GA_Result(); } public void Init_Group() { for (int i = 0; i < M; i++) { for (int j = 0; j < q_in.length + 1; j++) { if (j == 0 || j == q_in.length) { individual_Group_Old[i][j] = 0; } else { int k; k = new Random().nextInt(V.length); individual_Group_Old[i][j] = k; // 取得是整数编码的基因——映射库容值，比如存的是45，则对应的库容值是V[45] } } } } double[] E_SYZhi = new double[M]; public void Evaluate_Group(int t) { double[][] xie_chuku = new double[M][q_in.length]; // 出库流量(m3/s) double[][] xie_q = new double[M][q_in.length]; // 发电引用流量(m3/s) double[][] q_loss = new double[M][q_in.length]; // 弃水流量(m3/s) double[][] q_punishment = new double[M][q_in.length]; // 放惩罚水的电量 for (int i = 0; i < M; i++) { // System.out.println(); for (int j = 0; j < q_in.length; j++) { xie_chuku[i][j] = ( (V[individual_Group_Old[i][j]] - V[individual_Group_Old[i][j + 1]]) * Math .pow(10, 8)) / (30 * 24 * 3600) + q_in[j]; xie_q[i][j] = xie_chuku[i][j]; if (xie_chuku[i][j] < 0) { xie_chuku[i][j] = 0; xie_q[i][j] = 0; q_punishment[i][j] = a * Math.pow(t, b) * Math.pow(xie_chuku[i][j], (double) 2); } if (xie_chuku[i][j] > N_MaxQ) { // q_loss[i][j] = xie_chuku[i][j] - N_MaxQ; xie_q[i][j] = N_MaxQ; q_punishment[i][j] = a * Math.pow(t, b) * Math.pow(xie_chuku[i][j] - N_MaxQ, (double) 2); } } } // 求泄流量对应的库尾水位 double[][] H_damxia = new ChaZhi().KuWeiShuiWei(xie_q, ib, iq, M); // 求水头差 double[][] H_loss = new double[M][q_in.length]; for (int i = 0; i < M; i++) { for (int j = 0; j < q_in.length; j++) { H_loss[i][j] = (H_Cshuiwei[individual_Group_Old[i][j]] + H_Cshuiwei[individual_Group_Old[i][j + 1]]) / 2 - H_damxia[i][j]; } } // 求适应值 double[][] n_ChuLi = new double[M][q_in.length]; // kW double[][] E_n_ChuLi = new double[M][q_in.length]; // kW for (int i = 0; i < M; i++) { for (int j = 0; j < q_in.length; j++) { n_ChuLi[i][j] = A * xie_q[i][j] * H_loss[i][j] / Math.pow(10, 4); // 万kW E_n_ChuLi[i][j] = n_ChuLi[i][j] * 30 * 24 * Math.pow(10, 4) - q_punishment[i][j]; if (n_ChuLi[i][j] > N_Maxzhji) { xie_q[i][j] = n_ChuLi[i][j] * Math.pow(10, 4) / (A * H_loss[i][j]); // q_loss[i][j]=xie_chuku[i][j]-xie_q[i][j]; n_ChuLi[i][j] = N_Maxzhji; xie_q[i][j] = n_ChuLi[i][j] * Math.pow(10, 4) / (A * H_loss[i][j]); // zhongjie = n_ChuLi[i][j] * 30 * 24 * Math.pow(10, // 4);//要不要惩罚 E_n_ChuLi[i][j] = n_ChuLi[i][j] * 30 * 24 * Math.pow(10, 4) - a * Math.pow(t, b) * Math.pow(N_Maxzhji - n_ChuLi[i][j], (double) 2); } if (n_ChuLi[i][j] < N_Minzhji) { E_n_ChuLi[i][j] = n_ChuLi[i][j] * 30 * 24 * Math.pow(10, 4) - a * Math.pow(t, b) * Math.pow(N_Minzhji - n_ChuLi[i][j], (double) 2); } q_loss[i][j] = xie_chuku[i][j] - xie_q[i][j]; } } // 存放每代群体中个体的适应值 for (int i = 0; i < M; i++) { E_SYZhi[i] = 0; for (int j = 0; j < q_in.length; j++) { E_SYZhi[i] += E_n_ChuLi[i][j]; } } // 找出最佳个体及相应的指标 double max_E = 0; int Sign_xiabiao = 0; for (int i = 0; i < M; i++) { if (E_SYZhi[i] > max_E) { max_E = E_SYZhi[i]; Sign_xiabiao = i; } } optimal_E[t - 1] = max_E; if (t == T) { for (int j = 0; j < q_in.length; j++) { // 出库流量 optimal_chuku_Q[j] = xie_chuku[Sign_xiabiao][j]; loss_Q[j] = q_loss[Sign_xiabiao][j]; optimal_N_Q[j] = xie_q[Sign_xiabiao][j]; optimal_N[j] = n_ChuLi[Sign_xiabiao][j]; } for (int j = 0; j < q_in.length + 1; j++) { // 出库流量 optimal_H[j] = H_Cshuiwei[individual_Group_Old[Sign_xiabiao][j]]; } } } int[] lable = new int[M]; public void Select() { HashMap map = new HashMap(); for (int i = 0; i < E_SYZhi.length; i++) { map.put(new Double(E_SYZhi[i]), new Integer(i)); // 将值和下标存入Map } // 降序排列 Arrays.sort(E_SYZhi); // 查找原始下标 for (int i = 0; i < E_SYZhi.length; i++