A travelling salesman aims to visit a predetermined number of locations exactly once while taking the shortest route back to the beginning point in order to maximize sales.
The task is to determine the best path between vertices in a graph G = (V, E), where each destination, including the starting point, is a vertex, and if there is a direct route that connects two distinct destinations then there is an edge between those two vertices.
When a Hamiltonian Cycle—a shortest path that passes through every location and enables the salesman to return home—is found, the Travelling Salesman Problem (TSP) is solved. While there is still no universal solution for TSP, there are a number of local algorithms that can help.
The shortest path for the travelling salesman is visualized and found using a combination of graph algorithms in this work, guaranteeing that each place is only visited once before returning to the starting point.
I will be exploring graph algorithms namely: I.Breadth-first search II.Depth-first search III.Djikstra’s algorithm