Java使用google-ortools库的方法

1）加载动态链接

这个是windows环境，就是后缀为.dll的文件；

2）把下载的文件拷贝到C:\Windows\System32目录下

3）加载一下maven依赖，如:

 
      io.github.oliviercailloux
      google-or-tools
      6.7.2
 

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准备工作做好了，现在就可以跑Java程序了，如下例子：

import com.google.ortools.linearsolver.MPConstraint;
import com.google.ortools.linearsolver.MPObjective;
import com.google.ortools.linearsolver.MPSolver;
import com.google.ortools.linearsolver.MPVariable;

/** Simple linear programming example.*/
public class LinearProgrammingExample {
  static {
    System.loadLibrary("jniortools");
  }

  public static void main(String[] args) throws Exception {
    MPSolver solver = new MPSolver(
        "LinearProgrammingExample", MPSolver.OptimizationProblemType.GLOP_LINEAR_PROGRAMMING);

    double infinity = java.lang.Double.POSITIVE_INFINITY;
    // x and y are continuous non-negative variables.
    MPVariable x = solver.makeNumVar(0.0, infinity, "x");
    MPVariable y = solver.makeNumVar(0.0, infinity, "y");
    System.out.println("Number of variables = " + solver.numVariables());

    // x + 2*y <= 14.
    MPConstraint c0 = solver.makeConstraint(-infinity, 14.0, "c0");
    c0.setCoefficient(x, 1);
    c0.setCoefficient(y, 2);

    // 3*x - y >= 0.
    MPConstraint c1 = solver.makeConstraint(0.0, infinity, "c1");
    c1.setCoefficient(x, 3);
    c1.setCoefficient(y, -1);

    // x - y <= 2.
    MPConstraint c2 = solver.makeConstraint(-infinity, 2.0, "c2");
    c2.setCoefficient(x, 1);
    c2.setCoefficient(y, -1);
    System.out.println("Number of constraints = " + solver.numConstraints());

    // Maximize 3 * x + 4 * y.
    MPObjective objective = solver.objective();
    objective.setCoefficient(x, 3);
    objective.setCoefficient(y, 4);
    objective.setMaximization();

    final MPSolver.ResultStatus resultStatus = solver.solve();
    // Check that the problem has an optimal solution.
    if (resultStatus != MPSolver.ResultStatus.OPTIMAL) {
      System.err.println("The problem does not have an optimal solution!");
      return;
    }

    // The value of each variable in the solution.
    System.out.println("Solution");
    System.out.println("x = " + x.solutionValue());
    System.out.println("y = " + y.solutionValue());

    // The objective value of the solution.
    System.out.println("Optimal objective value = " + solver.objective().value());
  }
}

线性规划图如下： 

                         

 最后得到的值：

Number of variables = 2
Number of constraints = 3
Solution:
x = 6.0
y = 4.0
Optimal objective value = 34.0