LocalSolver(3) : データベースの連携と結果格納

Knapsack問題を利用し、最適拠点配置を行う。全部で４２拠点あるのでまず初期拠点をKnapsackで選び出し、閉鎖型待ち行列ネットワークで計算する。

１．パラメタ設定：人気度、拠点利用コスト、コスト制限
２．Knapsackで拠点算出->DBに登録
登録用テーブル
knapsacks

 elements

３．最適化計算->結果をテーブルに格納
価値：人気
重さ：拠点使用コスト

$ sudo vi Knapsack02.java
$ sudo javac Knapsack02.java -cp /opt/localsolver_5_5/bin/localsolver.jar
$ sudo java -cp /Users/mizuno/Desktop/work/mysql-connector-java-5.1.21-bin.jar:/opt/localsolver_5_5/bin/localsolver.jar:. -Djava.library.path=/opt/localsolver_5_5/bin/ Knapsack02

 


[Knapsack02.java]

********** Knapsack02.java **********/
import java.sql.*;
import java.util.*;
import java.io.*;
import localsolver.*;

public class Knapsack02 {
    /* Number of items. */
    int nbItems;

    /* Items properties. */
    int[] weights;
    int[] values;

    public int[] getValues(){ return this.values;}
    public int[] getWeights(){ return this.weights;}

    /* Knapsack bound */
    int knapsackBound;

    /* Solver. */
    LocalSolver localsolver;

    /* LS Program variables. */
    LSExpression[] x;

    /* Solutions (classes at each position). */
    List solutions;

    public Knapsack02(int nbItems, int knapsackBound, MySQL mysql){
        ResultSet rs = mysql.selectFacilities();
        this.nbItems = nbItems;
        weights = new int[nbItems];
        values = new int[nbItems];
        this.knapsackBound = knapsackBound;
        int index = 0;
        try {
                while(rs.next()){
                        values[index] = rs.getInt("popularity");
                        weights[index] = rs.getInt("cost");
                        index++;
                }
        }catch (SQLException e) {
                        e.printStackTrace();
        }


    }


    /* Reads instance data. */
    void readInstance(String fileName) {
        try {
            Scanner input = new Scanner(new File(fileName));

            nbItems = input.nextInt();

            weights = new int[nbItems];
            for (int i = 0; i < nbItems; i++) {
                weights[i] = input.nextInt();
            }

            values = new int[nbItems];
            for (int i = 0; i < nbItems; i++) {
                values[i] = input.nextInt();
            }

            knapsackBound = input.nextInt();

            input.close();

        } catch (IOException ex) {
            ex.printStackTrace();
        }
    }

    void solve(int limit) {
        try {
            /* Declares the optimization model. */
            localsolver = new LocalSolver();
            LSModel model = localsolver.getModel();
            x = new LSExpression[nbItems];

            System.out.println("nbItems="+nbItems);
            System.out.println("knapsackBound="+knapsackBound);

            // boolean variables x[i]
            for (int i = 0; i < nbItems; i++) {
                x[i] = model.boolVar();
                x[i].setName("x[" + i + "]");
            }

            // weight constraint
            LSExpression weightSum = model.sum();
            for (int i = 0; i < nbItems; i++) {
                LSExpression itemWeight = model.prod(x[i],weights[i]);
                weightSum.addOperand(itemWeight);
            }
            model.constraint(model.leq(weightSum,knapsackBound));

            // maximize value
            LSExpression valueSum = model.sum();
            for (int i = 0; i < nbItems; i++) {
                LSExpression itemValue = model.prod(x[i],values[i]);
                valueSum.addOperand(itemValue);
            }

            model.maximize(valueSum);
            model.close();

            /* Parameterizes the solver. */
            LSPhase phase = localsolver.createPhase();
            phase.setTimeLimit(limit);

            localsolver.solve();

            solutions = new ArrayList();
            for (int i = 0; i < nbItems; i++)
                if (x[i].getValue() == 1)
            solutions.add(i);

        } catch (LSException e) {
            System.out.println("LSException:" + e.getMessage());
            System.exit(1);
        }
    }

    /* Writes the solution in a file */
    void writeSolution(String fileName, MySQL mysql) {
        try {
            BufferedWriter output = new BufferedWriter(new FileWriter(fileName));

            int idx[] = new int[solutions.size()];
            double obj = 0;
            for (int i = 0; i < solutions.size(); ++i){
                output.write(solutions.get(i) + " ");
                idx[i] = solutions.get(i);
                obj += values[solutions.get(i)];
            }
            mysql.insertKnapsack(solutions.size(),obj);
            mysql.insertElement(idx);
            output.write("\n");

            output.close();
        } catch (IOException ex) {
            ex.printStackTrace();
        }
    }

     public static void main(String[] args) {

        int id = 1001;
        String outputFile = "result.txt";
        MySQL mysql = new MySQL(id);
        Knapsack02 model = new Knapsack02(42, 2000, mysql);
        //model.readInstance(instanceFile);
        String strTimeLimit = "10";
        int values[] = model.getValues();
        int weights[] = model.getWeights();
        for(int i = 0; i < 42; i++) System.out.print(weights[i]+" ");
        System.out.println("");
        for(int i = 0; i < 42; i++) System.out.print(values[i]+" ");
        System.out.println("");

        model.solve(Integer.parseInt(strTimeLimit));
        if(outputFile != null) {
            model.writeSolution(outputFile, mysql);
        }
    }
}