Determination of The Closest Path Using The Greedy Algorithm

Abstract

Several alternate routes are displayed by the greedy algorithm, which is widely used in the closest travel route search application. This study employs the greedy method, which sets up a route map to quickly determine the shortest path. The goal of this study is to find the shortest path using a greedy algorithm. By using a greedy algorithm system to find the closest point to which the user's selection is made, the study's eight times with different points on the graph can be seen in the user's position. In an attempt to find the best solution, the greedy algorithm—which is renowned for its simplicity and effectiveness—iteratively chooses the best option available at each step. The greedy algorithm frequently gives priority to proximity when it comes to travel route optimization, and it might not always produce the shortest path overall. However, it's a well-liked option for some applications due to its quickness and simplicity of implementation. Notwithstanding its drawbacks, the greedy algorithm can offer insightful solutions for optimization and route planning issues. Users can make decisions more quickly and possibly find alternate routes they might not have otherwise thought of by using this algorithm to find the closest point in a travel route search application. The study's conclusions also emphasize how crucial it is to take user convenience and preferences into account when developing route planning systems. Future studies could look into ways to improve the greedy algorithm's performance and fix its drawbacks, like adding more heuristics or combining it with other optimization strategies. Overall, this study's findings validate the greedy algorithm's efficacy as a workable choice for locating the closest point in travel route search applications, providing consumers with a dependable and approachable navigational aid.