diff --git a/Competitive Coding/Dynamic Programming/0-1Knapsack/knapsack.java b/Competitive Coding/Dynamic Programming/0-1Knapsack/knapsack.java
new file mode 100644
index 000000000..c7bae600d
--- /dev/null
+++ b/Competitive Coding/Dynamic Programming/0-1Knapsack/knapsack.java	
@@ -0,0 +1,70 @@
+import java.util.*;
+
+
+class Knapsack
+{
+ 
+ // A function to return maximum of two integers
+ static int maximum(int a, int b) 
+ {
+ if(a>b) 
+ return a; 
+ else 
+ return 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)
+ {
+ int i, w;
+ int K[][] = new int[n+1][W+1];
+ 
+ // Build table K[][] in bottom up manner
+ for (i = 0; i <= n; i++)
+ {
+ for (w = 0; w <= W; w++)
+ {
+ if (i==0 &#124;&#124; w==0)
+ K[i][w] = 0;
+ else if (wt[i-1] <= w)
+ K[i][w] = maximum(val[i-1] + K[i-1][w-wt[i-1]] , K[i1][w]);
+ else
+ K[i][w] = K[i-1][w];
+ }
+ }
+ 
+ Return K[n][W];
+ }
+ 
+ 
+ 
+ public static void main(String args[])
+ {
+		 
+ Scanner s=new Scanner(System.in);
+ System.out.println(&quot;Enter number of objects&quot;);
+ int n=s.nextInt();
+ int val[]=new int[n];
+ int wt[] = new int[n];
+ System.out.println(&quot;Enter values of objects&quot;);
+
+
+ for(int i=0;i<n;i++)
+ {
+ val[i]=s.nextInt();
+ }
+
+ System.out.println(&quot;Enter weights of object&quot;);
+ for(int i=0;i<n;i++)
+ {
+ wt[i]=s.nextInt();
+ }
+
+
+ System.out.println(&quot;Enter the maximum weight&quot;);
+ int W = s.nextInt();
+ System.out.println(knapSack(W, wt, val, n));
+ }
+}
+
diff --git a/Competitive Coding/Dynamic Programming/0-1Knapsack/readme.md b/Competitive Coding/Dynamic Programming/0-1Knapsack/readme.md
new file mode 100644
index 000000000..7e82b11cc
--- /dev/null
+++ b/Competitive Coding/Dynamic Programming/0-1Knapsack/readme.md	
@@ -0,0 +1,7 @@
+# 0-1 Knapsack
+The knapsack problem or rucksack problem is a problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items.
+
+**Time Complexity**
+Time Complexity: O(nW) where n is the number of items and W is the capacity of knapsack.
+### Applications
+Knapsack problems appear in real-world decision-making processes in a wide variety of fields, such as finding the least wasteful way to cut raw materials,[4] selection of investments and portfolios selection of assets for asset-backed securitization and generating keys for the Merkle–Hellman and other knapsack cryptosystems
</div><div class="naked_ctrl">
<form action="/index.cgi/contrast" method="get" name="gate">
<p><a href="http://altstyle.alfasado.net">AltStyle</a> によって変換されたページ <a href="https://patch-diff.githubusercontent.com/raw/codeIIEST/Algorithms/pull/200.diff">(-&gt;オリジナル)</a>
/ <label>アドレス: <input type="text" name="naked_post_url" value="https://patch-diff.githubusercontent.com/raw/codeIIEST/Algorithms/pull/200.diff" size="22" /></label> <label>モード: <select name="naked_post_mode">
<option value="default">デフォルト</option>
<option value="speech">音声ブラウザ</option>
<option value="ruby">ルビ付き</option>
<option value="contrast" selected="selected">配色反転</option>
<option value="larger-text">文字拡大</option>
<option value="mobile">モバイル</option>
</select>
<input type="submit" value="表示" />
</p>
</form>
</div>