Created Knapsack Problem

Java/floyd_warshal.java

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+import java.lang.*;
+
+class AllPairShortestPath {
+    private final static int INF = 99999, V = 4;
+
+    private void floydWarshall(int[][] graph) {
+        int[][] dist = new int[V][V];
+        int i, j, k;
+
+        for (i = 0; i < V; i++)
+            for (j = 0; j < V; j++)
+                dist[i][j] = graph[i][j];
+
+        for (k = 0; k < V; k++) {
+            // Pick all vertices as source one by one
+            for (i = 0; i < V; i++) {
+                for (j = 0; j < V; j++) {
+
+                    if (dist[i][k] + dist[k][j] < dist[i][j])
+                        dist[i][j] = dist[i][k] + dist[k][j];
+                }
+            }
+        }
+
+        // Print the shortest distance matrix
+        printSolution(dist);
+    }
+
+    private void printSolution(int[][] dist) {
+        System.out.println("The following matrix shows the shortest " +
+                "distances between every pair of vertices");
+        for (int i = 0; i < V; ++i) {
+            for (int j = 0; j < V; ++j) {
+                if (dist[i][j] == INF)
+                    System.out.print("INF ");
+                else
+                    System.out.print(dist[i][j] + "   ");
+            }
+            System.out.println();
+        }
+    }
+
+    public static void main(String[] args) {
+        int[][] graph = {{0, 5, INF, 10},
+                {INF, 0, 3, INF},
+                {INF, INF, 0, 1},
+                {INF, INF, INF, 0}
+        };
+        AllPairShortestPath a = new AllPairShortestPath();
+
+        a.floydWarshall(graph);
+    }
+} 

Python/0-1_Knapsack_Problem.py

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+''' Similar to fractional KnapSack except 
+you cannot break an item, 
+either pick the complete item, 
+or don’t pick it (0-1 property).'''
+
+def maxKnapSack(W , wt , profit , n): 
+
+    if n == 0 or W == 0 : 
+        return 0
+
+    # If weight of item is more than capacity W
+    # then this item cannot be included in the optimal solution 
+
+    if (wt[n-1] > W): 
+        return maxKnapSack(W , wt , profit , n-1) 
+
+    # return the maximum of two cases: 
+    # (a) item included 
+    # (b) not included 
+    else: 
+        return max(profit[n-1] + maxKnapSack(W-wt[n-1] , wt , profit , n-1), 
+                   maxKnapSack(W , wt , profit , n-1)) 
+
+# Driver Program
+if __name__ == '__main__':
+    profit = [60, 100, 120] 
+    wt = [10, 20, 30] 
+    W = 50
+    n = len(profit) 
+    print(maxKnapSack(W , wt , profit , n))