如何在spring boot应用程序中包含google OR-tools？

在Spring Boot应用程序中包含Google OR-Tools，可以按照以下步骤进行：

基础概念

Google OR-Tools（Operations Research Tools）是一套用于解决各种优化问题的库，包括线性规划、整数规划、约束满足问题等。

类型与应用场景

线性规划：资源分配、生产计划等。
整数规划：调度问题、旅行商问题等。
约束满足问题：排课系统、电路设计等。

包含步骤

1. 添加依赖

在pom.xml文件中添加OR-Tools的依赖：

<dependency>
    <groupId>com.google.ortools</groupId>
    <artifactId>ortools-java</artifactId>
    <version>9.3.10497</version>
</dependency>

2. 配置Maven仓库

确保你的pom.xml中包含了正确的Maven仓库地址：

<repositories>
    <repository>
        <id>google-releases</id>
        <url>https://oss.sonatype.org/content/repositories/google-releases/</url>
    </repository>
</repositories>

3. 编写示例代码

以下是一个简单的线性规划示例：

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

public class LinearProgrammingExample {
    public static void main(String[] args) {
        MPSolver solver = MPSolver.createSolver("GLOP_LINEAR_PROGRAMMING");
        if (solver == null) {
            System.out.println("Could not create solver GLOP_LINEAR_PROGRAMMING");
            return;
        }

        double infinity = java.lang.Double.POSITIVE_INFINITY;
        MPVariable x = solver.makeNumVar(0.0, infinity, "x");
        MPVariable y = solver.makeNumVar(0.0, infinity, "y");

        MPConstraint c0 = solver.makeConstraint(-x + y <= 1);
        MPConstraint c1 = solver.makeConstraint(x + y <= 2);

        MPObjective objective = solver.objective();
        objective.setCoefficient(x, 1);
        objective.setCoefficient(y, 1);
        objective.setMaximization();

        final MPSolver.ResultStatus resultStatus = solver.solve();

        if (resultStatus == MPSolver.ResultStatus.OPTIMAL) {
            System.out.println("Solution:");
            System.out.println("Objective value = " + objective.value());
            System.out.println("x = " + x.solutionValue());
            System.out.println("y = " + y.solutionValue());
        } else {
            System.out.println("The problem does not have an optimal solution!");
        }
    }
}