feat: knapsack-dynamic-programming challenge

Author: IbatoLionDev

2-NORMAL/Python/4-knapsack-dynamic-programming/proposed-solution/__pycache__/knapsack.cpython-312.pyc

@@ -0,0 +1,12 @@
+def knapsack(weights, values, capacity):
+    n = len(weights)
+    dp = [[0 for _ in range(capacity + 1)] for _ in range(n + 1)]
+
+    for i in range(1, n + 1):
+        for w in range(capacity + 1):
+            if weights[i-1] <= w:
+                dp[i][w] = max(values[i-1] + dp[i-1][w - weights[i-1]], dp[i-1][w])
+            else:
+                dp[i][w] = dp[i-1][w]
+
+    return dp[n][capacity]

2-NORMAL/Python/4-knapsack-dynamic-programming/proposed-solution/knapsack.py

@@ -0,0 +1,14 @@
+# Challenge: Solve the 0/1 knapsack problem using dynamic programming.
+# Given a set of items with weights and values, determine the combination that maximizes value without exceeding the capacity.
+
+from knapsack import knapsack
+
+def main():
+    weights = [2, 3, 4, 5]
+    values = [3, 4, 5, 6]
+    capacity = 5
+    max_value = knapsack(weights, values, capacity)
+    print(f"Maximum value in knapsack with capacity {capacity}: {max_value}")
+
+if __name__ == "__main__":
+    main()