PHP code example of kerigard / lpsolve

    
        
<?php
require_once('vendor/autoload.php');

/* Start to develop here. Best regards https://php-download.com/ */

    

kerigard / lpsolve example snippets

use Kerigard\LPSolve\Constraint;
use Kerigard\LPSolve\Problem;
use Kerigard\LPSolve\Solver;

$problem = new Problem(
    objective: [143, 60, 195],
    constraints: [
        new Constraint([120, 210, 150.75], LE, 15000),
        new Constraint([110, 30, 125], LE, 4000),
        new Constraint([1, 1, 1], LE, 75),
    ]
);

$solver = new Solver(Solver::MAX);
$solution = $solver->solve($problem);

var_dump($solution->getStatus()); // OPTIMAL solution
var_dump($solution->getCount()); // 1
var_dump($solution->getIterations()); // 2

if ($solution->getCode() === OPTIMAL) {
    var_dump($solution->getObjective()); // 6986.842105...
    var_dump($solution->getVariables()); // [0, 56.578947..., 18.421052...]
}

$problem = new Problem(
    objective: [-1, -2, 0.1, 3],
    constraints: [
        new Constraint([1, 1, 0, 0], LE, 5),
        new Constraint([2, -1, 0, 0], GE, 0),
        new Constraint([-1, 3, 0, 0], GE, 0),
        new Constraint([0, 0, 1, 1], GE, 0.5),
    ],
    lowerBounds: [0, 0, 1.1, 0],
    upperBounds: []
);

$solver = new Solver(Solver::MIN);
$solution = $solver->setScaling(SCALE_MEAN | SCALE_INTEGERS)->solve($problem);

var_dump($solution->getObjective()); // -8.223333...

$problem = new Problem(
    objective: [-1, -2, 0.1, 3],
    constraints: [
        new Constraint([1, 1, 0, 0], LE, 5),
        new Constraint([2, -1, 0, 0], GE, 0),
        new Constraint([-1, 3, 0, 0], GE, 0),
        new Constraint([0, 0, 1, 1], GE, 0.5),
    ],
    integerVariables: [0, 0, 1, 0], // integer variables (only variable #3 is integer)
    binaryVariables: [1, 0, 0, 1] // binary variables (variables #1 and #4 are binary)
);

$solver = new Solver(Solver::MIN);
$solution = $solver->setVerbose(DETAILED)->solve($problem);

var_dump($solution->getVariables()); // [1, 2, 1, 0]

$problem = new Problem(
    [1],
    [new Constraint([0, 78.26, 0, 2.9], GE, 92.3)]
);

try {
    $solver = new Solver();
    $solver->setTimeout(0)->solve($problem);
} catch (\LPSolveException $e) {
    var_dump($e->getMessage()); // Invalid vector
}

$problem = new Problem(
    [10, 10],
    [
        Constraint::fromString('1x + 1y = 20'),
        Constraint::fromString('0x + 1y <= 5'),
        Constraint::fromString('1x + 0y <= 5'),
    ]
);

try {
    $solver = new Solver(Solver::MIN);
    $solver->throw()->solve($problem);
} catch (\LPSolveException $e) {
    var_dump($e->getMessage()); // Model is primal INFEASIBLE
    var_dump($e->getCode() === INFEASIBLE); // true
}

$problem = new Problem(
    [1, 3, 6.24, 0.1],
    [
        new Constraint([0, 78.26, 0, 2.9], GE, 92.3),
        new Constraint([0.24, 0, 11.31, 0], LE, 14.8),
        new Constraint([12.68, 0, 0.08, 0.9], GE, 4),
    ]
);

$solver = (new Solver())
    ->beforeSolve(function ($lpsolve, $problem) {
        lpsolve('set_improve', $lpsolve, IMPROVE_SOLUTION);
    })
    ->afterSolve(function ($lpsolve, $problem, $solution) {
        lpsolve('write_lp', $lpsolve, 'model.lp');
    });

$solution = $solver->solve($problem);