JOptimizer解决LP问题

JOptimizer解决LP问题

可以使用JOptimizer来解决LP问题

<dependency>
    <groupId>com.joptimizer</groupId>
    <artifactId>joptimizer</artifactId>
    <version>5.0.0</version>
</dependency>

解决问题

/** minimize 4x+3Y 
* Subject to 
* 8x+6y <= 25 
* 3x+4y >= 15 
* x,y >= 0 
*/

代码如下

LinearMultivariateRealFunction objectiveFunction = new LinearMultivariateRealFunction(new double[]{4.0, 3.0}, 0); //minimize 4x+3y

        ConvexMultivariateRealFunction[] inequalities = new ConvexMultivariateRealFunction[4];

        // 不等式中都以G.x < h的形式出现
//         x >= 0
        inequalities[0] = new LinearMultivariateRealFunction(new double[]{-1.0, 0.00}, 0.0);
//         y >= 0
        inequalities[1] = new LinearMultivariateRealFunction(new double[]{0.0, -1.00}, 0.0);
//         8x+6y <= 25
        inequalities[2] = new LinearMultivariateRealFunction(new double[]{8, 6}, -25);
//         3x+4y >= 15
        inequalities[3] = new LinearMultivariateRealFunction(new double[]{-3, -4}, 15);

        OptimizationRequest or = new OptimizationRequest();
        or.setF0(objectiveFunction);
        or.setFi(inequalities);
//        or.setToleranceFeas(JOptimizer.DEFAULT_FEASIBILITY_TOLERANCE/10);
//        or.setTolerance(JOptimizer.DEFAULT_TOLERANCE/10);
//        or.setMaxIteration(2000);

        //optimization
        JOptimizer opt = new JOptimizer();
        opt.setOptimizationRequest(or);

        try {
            opt.optimize();
        } catch (Exception e) {
            e.printStackTrace();
        }

        if (opt.getOptimizationResponse() != null) {
            double[] sol = opt.getOptimizationResponse().getSolution();

            for (int i = 0; i < sol.length / 2; i++) {
                System.out.println("x" + (i + 1) + ": " + Math.round(sol[i]) + "\ty" + (i + 1) + ": " + Math.round(sol[i + 1]));
            }
        }

结果为

x1: 0    y1: 4