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DynamicProgramming/BruteForceKnapsack.java

@@ -15,15 +15,13 @@ public class BruteForceKnapsack {
   // capacity W
   static int knapSack(int W, int wt[], int val[], int n) {
     // Base Case
-		if (n == 0 || W == 0)
+    if (n == 0 || W == 0) return 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)
+    if (wt[n - 1] > W) return knapSack(W, wt, val, n - 1);
-			return knapSack(W, wt, val, n - 1);
 
     // Return the maximum of two cases:
     // (1) nth item included
@@ -34,8 +32,8 @@ public class BruteForceKnapsack {
 
   // Driver code
   public static void main(String args[]) {
-		int val[] = new int[] { 60, 100, 120 };
+    int val[] = new int[] {60, 100, 120};
-		int wt[] = new int[] { 10, 20, 30 };
+    int wt[] = new int[] {10, 20, 30};
     int W = 50;
     int n = val.length;
     System.out.println(knapSack(W, wt, val, n));

DynamicProgramming/DyanamicProgrammingKnapsack.java

@@ -16,12 +16,9 @@ public class DyanamicProgrammingKnapsack {
     // Build table K[][] in bottom up manner
     for (i = 0; i <= n; i++) {
       for (w = 0; w <= W; w++) {
-				if (i == 0 || w == 0)
+        if (i == 0 || w == 0) K[i][w] = 0;
-					K[i][w] = 0;
+        else if (wt[i - 1] <= w) K[i][w] = max(val[i - 1] + K[i - 1][w - wt[i - 1]], K[i - 1][w]);
-				else if (wt[i - 1] <= w)
+        else K[i][w] = K[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];
       }
     }
 
@@ -30,8 +27,8 @@ public class DyanamicProgrammingKnapsack {
 
   // Driver code
   public static void main(String args[]) {
-		int val[] = new int[] { 60, 100, 120 };
+    int val[] = new int[] {60, 100, 120};
-		int wt[] = new int[] { 10, 20, 30 };
+    int wt[] = new int[] {10, 20, 30};
     int W = 50;
     int n = val.length;
     System.out.println(knapSack(W, wt, val, n));

DynamicProgramming/MemoizationTechniqueKnapsack.java

@@ -3,32 +3,31 @@ package DynamicProgramming;
 // dynamic programming
 public class MemoizationTechniqueKnapsack {
 
-//A utility function that returns 
+  // A utility function that returns
-//maximum of two integers    
+  // maximum of two integers
   static int max(int a, int b) {
     return (a > b) ? a : b;
   }
 
-//Returns the value of maximum profit  
+  // Returns the value of maximum profit
   static int knapSackRec(int W, int wt[], int val[], int n, int[][] dp) {
 
     // Base condition
-		if (n == 0 || W == 0)
+    if (n == 0 || W == 0) return 0;
-			return 0;
 
-		if (dp[n][W] != -1)
+    if (dp[n][W] != -1) return dp[n][W];
-			return dp[n][W];
 
     if (wt[n - 1] > W)
 
       // Store the value of function call
       // stack in table before return
       return dp[n][W] = knapSackRec(W, wt, val, n - 1, dp);
-
     else
 
       // Return value of table after storing
-			return dp[n][W] = max((val[n - 1] + knapSackRec(W - wt[n - 1], wt, val, n - 1, dp)),
+      return dp[n][W] =
+          max(
+              (val[n - 1] + knapSackRec(W - wt[n - 1], wt, val, n - 1, dp)),
               knapSackRec(W, wt, val, n - 1, dp));
   }
 
@@ -39,17 +38,15 @@ public class MemoizationTechniqueKnapsack {
 
     // Loop to initially filled the
     // table with -1
-		for (int i = 0; i < N + 1; i++)
+    for (int i = 0; i < N + 1; i++) for (int j = 0; j < W + 1; j++) dp[i][j] = -1;
-			for (int j = 0; j < W + 1; j++)
-				dp[i][j] = -1;
 
     return knapSackRec(W, wt, val, N, dp);
   }
 
-//Driver Code
+  // Driver Code
   public static void main(String[] args) {
-		int val[] = { 60, 100, 120 };
+    int val[] = {60, 100, 120};
-		int wt[] = { 10, 20, 30 };
+    int wt[] = {10, 20, 30};
 
     int W = 50;
     int N = val.length;