package DynamicProgramming;

/* A Naive recursive implementation
of 0-1 Knapsack problem */
public class BruteForceKnapsack {

  // A utility function that returns
  // maximum of two integers
  static int max(int a, int b) {
    return (a > b) ? a : b;
  }

  // Returns the maximum value that
  // can be put in a knapsack of
  // capacity W
  static int knapSack(int W, int wt[], int val[], int n) {
    // Base Case
    if (n == 0 || W == 0) return 0;

    // If weight of the nth item is
    // more than Knapsack capacity W,
    // then this item cannot be included
    // in the optimal solution
    if (wt[n - 1] > W) return knapSack(W, wt, val, n - 1);

    // Return the maximum of two cases:
    // (1) nth item included
    // (2) not included
    else
      return max(val[n - 1] + knapSack(W - wt[n - 1], wt, val, n - 1), knapSack(W, wt, val, n - 1));
  }

  // Driver code
  public static void main(String args[]) {
    int val[] = new int[] {60, 100, 120};
    int wt[] = new int[] {10, 20, 30};
    int W = 50;
    int n = val.length;
    System.out.println(knapSack(W, wt, val, n));
  }
}