写出Java调用cplex的具体代码，解决刚刚的问题

好的，以下是一个简单的Java调用CPLEX求解VRP问题的示例代码：

import ilog.concert.*;
import ilog.cplex.*;

public class VRP {
  public static void main(String[] args) {
    try {
      // 创建 CPLEX 模型对象
      IloCplex cplex = new IloCplex();

      // 创建变量 x[i][j][k]，表示从客户 i 到客户 j 用车 k 进行配送的数量
      int numCustomers = 10;
      int numVehicles = 3;
      IloIntVar[][][] x = new IloIntVar[numCustomers+1][numCustomers+1][numVehicles+1];
      for (int i = 1; i <= numCustomers; i++) {
        for (int j = 1; j <= numCustomers; j++) {
          for (int k = 1; k <= numVehicles; k++) {
            x[i][j][k] = cplex.intVar(0, Integer.MAX_VALUE);
          }
        }
      }

      // 创建变量 y[j][k]，表示车 k 是否会访问客户 j
      IloIntVar[][] y = new IloIntVar[numCustomers+1][numVehicles+1];
      for (int j = 1; j <= numCustomers; j++) {
        for (int k = 1; k <= numVehicles; k++) {
          y[j][k] = cplex.boolVar();
        }
      }

      // 创建目标函数，最小化配送成本
      IloLinearNumExpr costExpr = cplex.linearNumExpr();
      for (int i = 1; i <= numCustomers; i++) {
        for (int j = 1; j <= numCustomers; j++) {
          for (int k = 1; k <= numVehicles; k++) {
            costExpr.addTerm(distance(i, j), x[i][j][k]);
          }
        }
      }
      cplex.addMinimize(costExpr);

      // 添加约束条件，每个客户必须被访问一次
      for (int j = 1; j <= numCustomers; j++) {
        IloLinearNumExpr visitExpr = cplex.linearNumExpr();
        for (int i = 1; i <= numCustomers; i++) {
          for (int k = 1; k <= numVehicles; k++) {
            visitExpr.addTerm(1, x[i][j][k]);
          }
        }
        cplex.addEq(visitExpr, 1);
      }

      // 添加约束条件，每辆车的容量不能超过限制
      int[] demand = {10, 20, 30, 10, 5, 15, 5, 10, 10, 5};
      int capacity = 50;
      for (int k = 1; k <= numVehicles; k++) {
        IloLinearNumExpr capacityExpr = cplex.linearNumExpr();
        for (int j = 1; j <= numCustomers; j++) {
          capacityExpr.addTerm(demand[j-1], y[j][k]);
          for (int i = 1; i <= numCustomers; i++) {
            capacityExpr.addTerm(-demand[j-1], x[i][j][k]);
          }
        }
        cplex.addLe(capacityExpr, capacity);
      }

      // 添加约束条件，车辆必须从总部出发并返回
      for (int k = 1; k <= numVehicles; k++) {
        IloLinearNumExpr originExpr = cplex.linearNumExpr();
        for (int j = 1; j <= numCustomers; j++) {
          originExpr.addTerm(1, y[j][k]);
          originExpr.addTerm(-1, y[0][k]);
        }
        cplex.addEq(originExpr, 0);
      }

      // 求解模型
      if (cplex.solve()) {
        // 输出结果
        System.out.println("Total cost: " + cplex.getObjValue());
        for (int i = 1; i <= numCustomers; i++) {
          for (int j = 1; j <= numCustomers; j++) {
            for (int k = 1; k <= numVehicles; k++) {
              if (cplex.getValue(x[i][j][k]) > 0.0001) {
                System.out.println("Vehicle " + k + " delivers " + cplex.getValue(x[i][j][k]) + " units from customer " + i + " to customer " + j);
              }
            }
          }
        }
      } else {
        System.out.println("No solution found.");
      }

      // 释放 CPLEX 资源
      cplex.end();
    } catch (IloException e) {
      System.err.println("Concert exception caught: " + e);
    }
  }

  // 计算客户 i 和客户 j 之间的距离
  private static double distance(int i, int j) {
    int[][] coordinates = {{0, 0}, {40, 50}, {45, 68}, {60, 70}, {70, 40}, {66, 20}, {30, 25}, {20, 30}, {15, 45}, {45, 35}, {35, 20}};
    int dx = coordinates[i][0] - coordinates[j][0];
    int dy = coordinates[i][1] - coordinates[j][1];
    return Math.sqrt(dx*dx + dy*dy);
  }
}

这个示例程序使用CPLEX求解VRP问题，并输出了每辆车的配送方案以及总成本。在这个示例中，您需要将CPLEX的Java API添加到您的项目依赖中，并按照示例中的方式创建模型、变量和约束条件。然后，您可以调用`cplex.solve()`方法来求解模型，并使用`cplex.getValue()`方法获取每个变量的值。