Linear Optimization with Kotlin and Apache Commons Math

linear_optimization.kt

package org.nield.kotlinstatistics

import org.apache.commons.math3.optim.MaxIter
import org.apache.commons.math3.optim.linear.*
import org.apache.commons.math3.optim.nonlinear.scalar.GoalType

/* 
Linear optimization with Apache Commons Math and Kotlin
Original problem: http://benalexkeen.com/linear-programming-with-python-and-pulp-part-3/
 */

fun main(args: Array<String>) {

    // describe the optimization problem
    val f = LinearObjectiveFunction(doubleArrayOf(30000.0, 45000.0), 0.0)

    val constraints = mutableListOf<LinearConstraint>()

    constraints.add(LinearConstraint(doubleArrayOf(1.0, 0.0), Relationship.GEQ, 0.0))
    constraints.add(LinearConstraint(doubleArrayOf(0.0, 1.0), Relationship.GEQ, 0.0))
    constraints.add(LinearConstraint(doubleArrayOf(3.0, 4.0), Relationship.LEQ, 30.0))
    constraints.add(LinearConstraint(doubleArrayOf(5.0, 6.0), Relationship.LEQ, 60.0))
    constraints.add(LinearConstraint(doubleArrayOf(1.5, 3.0), Relationship.LEQ, 21.0))


    // create and run the solver
    val solution = SimplexSolver().optimize(MaxIter(1000), f, LinearConstraintSet(constraints), GoalType.MAXIMIZE, NonNegativeConstraint(true))


    // get the solution
    val x = solution.point[0]
    val y = solution.point[1]
    val min = solution.value

    println("$x $y $min")
}