ejemplo de código de Python del problema de la mochila

Ejemplo 1: mochila python 0-1

#Returns the maximum value that can be stored by the bag

def knapSack(W, wt, val, n):
   # initial conditions
   if n == 0 or W == 0 :
      return 0
   # If weight is higher than capacity then it is not included
   if (wt[n-1] > W):
      return knapSack(W, wt, val, n-1)
   # return either nth item being included or not
   else:
      return max(val[n-1] + knapSack(W-wt[n-1], wt, val, n-1),
         knapSack(W, wt, val, n-1))
# To test above function
val = [50,100,150,200]
wt = [8,16,32,40]
W = 64
n = len(val)
print (knapSack(W, wt, val, n))

Ejemplo 2: algoritmo de mochila en python

# a dynamic approach
# Returns the maximum value that can be stored by the bag
def knapSack(W, wt, val, n):
   K = [[0 for x in range(W + 1)] for x in range(n + 1)]
   #Table in bottom up manner
   for i in range(n + 1):
      for w in range(W + 1):
         if i == 0 or w == 0:
            K[i][w] = 0
         elif wt[i-1] <= w:
            K[i][w] = max(val[i-1] + K[i-1][w-wt[i-1]], K[i-1][w])
         else:
            K[i][w] = K[i-1][w]
   return K[n][W]
#Main
val = [50,100,150,200]
wt = [8,16,32,40]
W = 64
n = len(val)
print(knapSack(W, wt, val, n))

Ejemplo 3: problema de la mochila

// memory efficient and iterative approach to the knapsack problem

#include <bits/stdc++.h>
using namespace std;

// n is the number of items
// w is the knapsack's capacity
int n, w;

int main() {
/*
input format:
n w
value_1 cost_1
value_2 cost_2
.
.
value_n cost_n
*/
    cin >> n >> w;
  	vector<long long> dp(w + 1, 0);

    for (int i = 0; i < n; ++i) {
        int value, cost;
        cin >> value >> cost;
        for (int j = w; j >= cost; --j)
            dp[j] = max(dp[j], value + dp[j - cost]);
    }

    // the answer is dp[w]
    cout << dp[w];
}

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