Choose items in a 0/1 backpack where two items have the same benefits | increase value and minimize weight

Question

In the backpack problem 0/1, how to select elements if two elements have the same value. You should choose a value with a lower weight, how can I check this condition? I have the following function using dynamic programming.

static int[] knapsack(int maxWeight, double[] weight, double[] value, int n) {
    //n = no. if items
    int i, w;

    double array[][] = new double[n + 1][maxWeight + 1];
    for (i = 0; i <= n; i++) {
        for (w = 0; w <= maxWeight; w++) {
            if (i == 0 || w == 0)
                array[i][w] = 0;
            else if (weight[i - 1] <= w)
                array[i][w] = max(value[i - 1] + array[i - 1][(w -(int) weight[i - 1])], array[i - 1][w]);
            else
                array[i][w] = array[i - 1][w];
            if (i != 0 || w != 0)
                System.out.print(array[i][w] + "\t");
        }
        System.out.println();
    }

    int[] selected = new int[n + 1];
    for (int j = n, wt = maxWeight; j > 0; j--) {   
        if (array[j][wt] != array[j - 1][wt]) {
            if (array[j][wt] == array[j][wt - 1]) {
                selected[j] = 0;
                break;
            }
            selected[j] = 1;
            wt = wt - (int) weight[j - 1];
        }
        else
            selected[j] = 0;
    }
    /** Print finally selected items **/
    System.out.println("\nItems selected : ");
    for (int k = 1; k < n + 1; k++)
        if (selected[k] == 1)
            System.out.print(k +" ");
        System.out.println();

        return selected;
}

For this type of case: (i, v): (4.45) (3.20) (5.30) (2.45), maxWeight = 5; where points 1 and 4 have the same meaning, he must choose an element with a lower weight, which is equal to the 4th. how to implement this condition in the above code. Description of the problem:

- , . , , .

Answer 1

. ,

DP [i] [j] - , !

W [i] [j] , !!

if(Current Weight > Element Weight)
{
      if(DP[i-1][j-Weight[i]]+Value[i]>DP[i-1][j]){
             DP[i][j]=DP[i-1][j-Weight[i]]+Value[i];
             Weight[i][j]= Weight[i-1][j-Weight[i]]+Value[i]
      }
      else if(DP[i-1][j-Weight[i]]+Value[i] <  DP[i-1][j] ){
             DP[i][j]=DP[i-1][j];
             Weight[i][j]=Weight[i-1][j];
      } 
      else{                   //Note this is the tricky part elsewise the 
                              //Above conditions are simple Knapsack conditions

             DP[i][j]=DP[i-1][j];   //Both of them are equal We will get same Value . Thus we cannot maximise it in any other way!!
             Weight[i][j]=minimum ( Weight[i-1][j] ,Weight[i-1][j-Weight[i]]+A[i]);

      }
}
else
{
             DP[i][j]=DP[i-1][j];
             Weight[i][j]=Weight[i-1][j];
}

, , ! ! ! , , . !

, 0/1, !!

Answer 2

, object[i] [i + 1], , , object[i] = object[i + 1] .. ?