This page is for an old version of Hexaly Optimizer. We recommend that you update your version and read the documentation for the latest stable release.

Hosaki Function

Note

This problem can be resolved without the surrogate modeling functionality (see branin function). Indeed, this functionality is useful when the objective function is computationally expensive. The purpose of this example is only to illustrate the use of surrogate modeling on a simple and computationally inexpensive problem.

Principles learned

  • Create an external function
  • Enable the surrogate modeling on an external function
  • Set an evaluation limit to the function

Problem

../_images/hosaki_blackbox.svg

Hosaki function is defined by

This is a box-constrained problem.

For more details, see: hosaki_function.html

Download the example


Program

The objective function is defined by an external function. It receives the argument values via the LSExternalArgumentValues, and returns the value of the function at this point.

Two floating decision variables x1 and x2 are declared. The domains of these variables are respectively [0,5] and [0,6]. To calculate the value returned by the external function, an O_Call expression is created. This expression is then minimized.

To use the surrogate modeling feature, the method enableSurrogateModeling available on the LSExternalContext of the function is called. This method returns the LSSurrogateParameters, on which the maximum number of calls to the function can be set, as the function is usually computationally expensive.

Execution:
localsolver hosaki.lsp [evaluationLimit=] [solFileName=]
use io;

/* External function */
function hosaki(x1, x2) {
    return (1 - 8*x1 + 7*pow(x1, 2) - 7*pow(x1, 3)/3 + pow(x1, 4)/4) * pow(x2, 2)
            * exp(-x2);
}

/* Declare the optimization model */
function model() {
    // Numerical decisions
    x1 <- float(0, 5);
    x2 <- float(0, 6);

    // Create and call the function
    f <- doubleExternalFunction(hosaki);
    funcCall <- call(f, x1, x2);

    // Enable surrogate modeling
    surrogateParams = f.context.enableSurrogateModeling();

    // Minimize function call
    minimize(funcCall);
}

/* Parameterize the solver */
function param() {
    if (evaluationLimit == nil) surrogateParams.evaluationLimit = 30;
    else surrogateParams.evaluationLimit = evaluationLimit;
}

/* Write the solution in a file */
function output() {
    if (solFileName != nil) {
        local solFile = io.openWrite(solFileName);
        solFile.println("obj=", funcCall.value);
        solFile.println("x1=", x1.value);
        solFile.println("x2=", x2.value);
    }
}
Execution (Windows)
set PYTHONPATH=%LS_HOME%\bin\python
python hosaki.py
Execution (Linux)
export PYTHONPATH=/opt/localsolver_12_5/bin/python
python hosaki.py
import localsolver
import sys
import math

#
# External function
#
def hosaki_function(argument_values):
    x1 = argument_values[0]
    x2 = argument_values[1]
    return ((1 - 8 * x1 + 7 * pow(x1, 2) - 7 * pow(x1, 3) / 3 + pow(x1, 4) / 4) 
            * pow(x2, 2) * math.exp(-x2))


def main(evaluation_limit, output_file):
    with localsolver.LocalSolver() as ls:
        #
        # Declare the optimization model
        #
        model = ls.model

        # Numerical decisions
        x1 = model.float(0, 5)
        x2 = model.float(0, 6)

        # Create and call the function
        f = model.create_double_external_function(hosaki_function)
        func_call = model.call(f, x1, x2)

        # Enable surrogate modeling
        surrogate_params = f.external_context.enable_surrogate_modeling()

        # Minimize function call
        model.minimize(func_call)
        model.close()

        # Parameterize the solver
        surrogate_params.evaluation_limit = evaluation_limit

        ls.solve()

        # Write the solution in a file
        if output_file is not None:
            with open(output_file, 'w') as f:
                f.write("obj=%f\n" % func_call.value)
                f.write("x1=%f\n" % x1.value)
                f.write("x2=%f\n" % x2.value)


if __name__ == '__main__':
    output_file = sys.argv[1] if len(sys.argv) > 1 else None
    evaluation_limit = int(sys.argv[2]) if len(sys.argv) > 2 else 30

    main(evaluation_limit, output_file)
Compilation / Execution (Windows)
cl /EHsc hosaki.cpp -I%LS_HOME%\include /link %LS_HOME%\bin\localsolver125.lib
hosaki
Compilation / Execution (Linux)
g++ hosaki.cpp -I/opt/localsolver_12_5/include -llocalsolver125 -lpthread -o hosaki
hosaki
#include "localsolver.h"
#include <cmath>
#include <fstream>
#include <iostream>

using namespace localsolver;
using namespace std;

/* External function */
class HosakiFunction : public LSExternalFunction<lsdouble> {
    lsdouble call(const LSExternalArgumentValues& argumentValues) override {
        lsdouble x1 = argumentValues.getDoubleValue(0);
        lsdouble x2 = argumentValues.getDoubleValue(1);
        return (1 - 8 * x1 + 7 * pow(x1, 2) - 7 * pow(x1, 3) / 3 + pow(x1, 4) / 4) * pow(x2, 2) * exp(-x2);
    }
};

class Hosaki {
public:
    // LocalSolver
    LocalSolver localsolver;

    // LS Program variables
    LSExpression x1;
    LSExpression x2;
    LSExpression funcCall;

    void solve(int evaluationLimit) {
        // Declare the optimization model
        LSModel model = localsolver.getModel();

        // Numerical decisions
        x1 = model.floatVar(0, 5);
        x2 = model.floatVar(0, 6);

        // Create and call the function
        HosakiFunction funcClass;
        LSExpression func = model.createExternalFunction(&funcClass);
        funcCall = model.call(func, x1, x2);

        // Enable surrogate modeling
        LSExternalContext context = func.getExternalContext();
        LSSurrogateParameters surrogateParams = context.enableSurrogateModeling();

        // Minimize function call
        model.minimize(funcCall);
        model.close();

        // Parameterize the solver
        surrogateParams.setEvaluationLimit(evaluationLimit);

        localsolver.solve();
    }

    /* Write the solution in a file */
    void writeSolution(const string& fileName) {
        ofstream outfile;
        outfile.exceptions(ofstream::failbit | ofstream::badbit);
        outfile.open(fileName.c_str());
        outfile << "obj=" << funcCall.getDoubleValue() << endl;
        outfile << "x1=" << x1.getDoubleValue() << endl;
        outfile << "x2=" << x2.getDoubleValue() << endl;
    }
};

int main(int argc, char** argv) {
    const char* solFile = argc > 1 ? argv[1] : NULL;
    const char* strEvaluationLimit = argc > 2 ? argv[2] : "30";

    try {
        Hosaki model;
        model.solve(atoi(strEvaluationLimit));
        if (solFile != NULL)
            model.writeSolution(solFile);
    } catch (const exception& e) {
        cerr << "An error occurred: " << e.what() << endl;
        return 1;
    }
    return 0;
}
Compilation / Execution (Windows)
copy %LS_HOME%\bin\localsolvernet.dll .
csc Hosaki.cs /reference:localsolvernet.dll
Hosaki
using System;
using System.IO;
using localsolver;

public class Hosaki : IDisposable
{
    /* External function */
    public class HosakiFunction
    {
        public double Call(LSExternalArgumentValues argumentValues)
        {
            double x1 = argumentValues.GetDoubleValue(0);
            double x2 = argumentValues.GetDoubleValue(1);
            return (1 - 8 * x1 + 7 * Math.Pow(x1, 2) - 7 * Math.Pow(x1, 3) / 3 + Math.Pow(x1, 4) / 4)
                * Math.Pow(x2, 2)
                * Math.Exp(-x2);
        }
    }

    // LocalSolver
    private LocalSolver localsolver;

    // LS Program variables
    private LSExpression x1;
    private LSExpression x2;
    private LSExpression funcCall;

    public Hosaki()
    {
        localsolver = new LocalSolver();
    }

    public void Dispose()
    {
        if (localsolver != null)
            localsolver.Dispose();
    }

    public void Solve(int evaluationLimit)
    {
        // Declare the optimization model
        LSModel model = localsolver.GetModel();

        // Numerical decisions
        x1 = model.Float(0, 5);
        x2 = model.Float(0, 6);

        // Create and call the function
        HosakiFunction hosakiFunction = new HosakiFunction();
        LSDoubleExternalFunction func = new LSDoubleExternalFunction(hosakiFunction.Call);
        LSExpression funcExpr = model.DoubleExternalFunction(func);
        funcCall = model.Call(funcExpr, x1, x2);

        // Enable surrogate modeling
        LSExternalContext context = funcExpr.GetExternalContext();
        LSSurrogateParameters surrogateParams = context.EnableSurrogateModeling();

        // Minimize function call
        model.Minimize(funcCall);
        model.Close();

        // Parameterize the solver
        surrogateParams.SetEvaluationLimit(evaluationLimit);

        localsolver.Solve();
    }

    /* Write the solution in a file */
    public void WriteSolution(string fileName)
    {
        using (StreamWriter output = new StreamWriter(fileName))
        {
            output.WriteLine("obj=" + funcCall.GetDoubleValue());
            output.WriteLine("x1=" + x1.GetDoubleValue());
            output.WriteLine("x2=" + x2.GetDoubleValue());
        }
    }

    public static void Main(string[] args)
    {
        string outputFile = args.Length > 0 ? args[0] : null;
        string strEvaluationLimit = args.Length > 1 ? args[1] : "30";

        using (Hosaki model = new Hosaki())
        {
            model.Solve(int.Parse(strEvaluationLimit));
            if (outputFile != null)
                model.WriteSolution(outputFile);
        }
    }
}
Compilation / Execution (Windows)
javac Hosaki.java -cp %LS_HOME%\bin\localsolver.jar
java -cp %LS_HOME%\bin\localsolver.jar;. Hosaki
Compilation / Execution (Linux)
javac Hosaki.java -cp /opt/localsolver_12_5/bin/localsolver.jar
java -cp /opt/localsolver_12_5/bin/localsolver.jar:. Hosaki
import java.io.*;
import java.lang.Math;
import localsolver.*;

public class Hosaki {

    /* External function */
    private static class HosakiFunction implements LSDoubleExternalFunction {
        @Override
        public double call(LSExternalArgumentValues argumentValues) {
            double x1 = argumentValues.getDoubleValue(0);
            double x2 = argumentValues.getDoubleValue(1);
            return (1 - 8 * x1 + 7 * Math.pow(x1, 2) - 7 * Math.pow(x1, 3) / 3 + Math.pow(x1, 4) / 4) * Math.pow(x2, 2) * Math.exp(-x2);
        }
    }

    // LocalSolver
    private final LocalSolver localsolver;

    // LS Program variables
    private LSExpression x1;
    private LSExpression x2;
    private LSExpression funcCall;

    private Hosaki(LocalSolver localsolver) {
        this.localsolver = localsolver;
    }

    private void solve(int evaluationLimit) {
        // Declare the optimization model
        LSModel model = localsolver.getModel();

        // Numerical decisions
        x1 = model.floatVar(0, 5);
        x2 = model.floatVar(0, 6);

        // Create and call the function
        HosakiFunction function = new HosakiFunction();
        LSExpression func = model.doubleExternalFunction(function);
        funcCall = model.call(func, x1, x2);

        // Enable surrogate modeling
        LSExternalContext context = func.getExternalContext();
        LSSurrogateParameters surrogateParams = context.enableSurrogateModeling();

        // Minimize function call
        model.minimize(funcCall);
        model.close();

        // Parameterize the solver
        surrogateParams.setEvaluationLimit(evaluationLimit);

        localsolver.solve();
    }

    /* Write the solution in a file */
    private void writeSolution(String fileName) throws IOException {
        try (PrintWriter output = new PrintWriter(fileName)) {
            output.println("obj=" + funcCall.getDoubleValue());
            output.println("x1=" + x1.getDoubleValue());
            output.println("x2=" + x2.getDoubleValue());
        }
    }

    public static void main(String[] args) {
        String outputFile = args.length > 0 ? args[0] : null;
        String strEvaluationLimit = args.length > 1 ? args[1] : "30";

        try (LocalSolver localsolver = new LocalSolver()) {
            Hosaki model = new Hosaki(localsolver);
            model.solve(Integer.parseInt(strEvaluationLimit));
            if (outputFile != null) {
                model.writeSolution(outputFile);
            }
        } catch (Exception ex) {
            System.err.println(ex);
            ex.printStackTrace();
            System.exit(1);
        }
    }
}