Repeated Nearest Neighbor Algorithm RNNA Explained | Graph Theory Basics #graphtheory

In this video, I explain the Repeated Nearest Neighbor Algorithm (RNNA), an extension of the Nearest Neighbor Algorithm used in Graph Theory to find the shortest path in problems like the Traveling Salesman Problem. This approach improves accuracy by comparing multiple circuits to find the optimal one.

Here are the steps we'll cover in this tutorial:

1. Run the Nearest Neighbor Algorithm from each vertex: We apply the Nearest Neighbor Algorithm starting from every vertex in the graph to generate different circuits.
2. Select the circuit with the smallest total weight: After computing all possible circuits, we choose the one with the minimum total edge weight.

By the end of this video, you'll know how to apply the Repeated Nearest Neighbor Algorithm to find better solutions for pathfinding problems in graph theory. Feel free to ask any questions or share your thoughts in the comments below!

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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Original text from Math in Society by David Lippman.