**Objective: **Given a 2D-matrix where each cell has a cost to travel. You have to write an algorithm to find a path from left-top corner to bottom-right corner with minimum travel cost. You can move only right or down.

In the solution we will see that how dynamic programming is much better approach than recursion. Don’t get me wrong, even I like recursion a lot 🙂

**Example**:

MInimum-Cost-Path-Problem

**Approach**:

This problem is similar to** Find all paths from top-left corner to bottom-right corner.**

We can solve it using Recursion ( return Min(path going right, path going down)) but that won’t be a good solution because we will be solving many sub-problems multiple times. Since at every cell we have 2 options the time complexity will O(2^{n}).

**Dynamic Programming:**

Create a solution matrix of the same size as given matrix.

We will fill this matrix in **Bottom-up** manner.

**Given**: arrA[][].

At every cell, we have two options (go right or down) and we will choose the minimum of these two.
So for any i,j cell
solution[i][j] = A[0][j] if i=0 , first row
= A[i][0] if j=0, first column
= A[i][j] + Min(solution[i-1],[j] , solution[i][j-1]) if i>0 && j>0
See the code for better Explanation.

Time Complexity: O(n^{2}).

**Code:**

**Output**:
Minimum Cost Path 29

*Related*