From c377c07b9891f9ef48eec8ae55e2a59b0341ee49 Mon Sep 17 00:00:00 2001
From: Edward Blake <141681072+Edd-P-P@users.noreply.github.com>
Date: Mon, 11 Dec 2023 22:56:02 -0600
Subject: [PATCH] Update README.md

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 1167c5a..d9721dc 100644
--- a/README.md
+++ b/README.md
@@ -76,7 +76,7 @@ M =
 In this scenario, our objective is to minimize the matrix M. It is straightforward to understand how distances are defined in this context. We can approach it row by row, considering the permutation $C = (0 \quad 1 \quad 2 \quad 3)$, where each number corresponds to a city, with 0 representing the origin city. For the given matrix, the cost of the route $C$ is 19. This calculation is derived from the fact that the journey from city 0 to city 1 incurs a cost of 3, and the journey from city 2 to city 3 incurs a cost of 6. Essentially, the row number represents the current city, and the column number represents the destination city. On the other hand, it is worth noting that in the trace of the matrix, we encounter 
 $\infty$. This is due to the fact that in Hamiltonian diagrams, the distance from a point to itself is defined as $\infty$.
 
-** Algotithm **
+**Algotithm**