Dijkstra‘s Algorithm for Effective Travelling
to the Most Famous Destinations in Myanmar

San San Maw; Khin Saw Lin; Lin Lin Naing

doi:https://doi.org/10.14445/22315373/IJMTT-V65I8P502

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 65 | Issue 8 | Year 2019 | Article Id. IJMTT-V65I8P502 | DOI : https://doi.org/10.14445/22315373/IJMTT-V65I8P502

Dijkstra‘s Algorithm for Effective Travelling to the Most Famous Destinations in Myanmar

San San Maw, Khin Saw Lin, Lin Lin Naing

Abstract

In this paper,the well-known Dijkstra’s Algorithm is applied to find the optimal paths for travelling to the most famous destinations in Myanmar. It is aSingle-Source Shortest Path (SSSP) iterative algorithm and the basic idea is searching a graph by findingpath, starting at a point, and exploring adjacent nodes from there until the destination node is reached. Generally, the goal is to obtain the shortest path from current city to the other destinations. This algorithm can bereviewed with values which come from weights on edges according to actual situations on the road, such as costs, distances, and travelling time. The key issue to be addressed in this work is to find the shortest paths from one source point (city/place) to others by comparing the weighted values (i.e., distances and time) between any two different paths with their edge lengths (roads) that assigned by actual values for saving cost and time for effective travelling. The values of distances and time between any two destinations are taken from Myanmar distance calculator website and compared the accuracy of the results using those values in Google Map.

Keywords

Path Finding, Weighted Graph, Routing, Shortest Paths, Dijkstra’s Algorithm.

References

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Citation :

San San Maw, Khin Saw Lin, Lin Lin Naing, "Dijkstra‘s Algorithm for Effective Travelling to the Most Famous Destinations in Myanmar," International Journal of Mathematics Trends and Technology (IJMTT), vol. 65, no. 8, pp. 4-12, 2019. Crossref, https://doi.org/10.14445/22315373/IJMTT-V65I8P502