A New Shortest Path Algorithm using Lists

In graph theory, the shortest path problem can be defined as a problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized. A topic that is revered in the field of graph theory and has numerous practical applications including vehicular routing, network designs, etc., the shortest path problem has had several notable approaches to it, including Floyd-Warshall Algorithm, Bellman-Ford Algorithm, and the most renowned Dijkstra's Algorithm. When I came across the algorithm behind Dijkstra's method of solving the shortest path problem in a weighted directed graph (though it can be applied to undirected graphs as well), I wondered if I could come up with my own algorithm for solving the problem using one of Python's data structures: Lists. After over a month of tens of trial-and-error attempts, my peer Syed Abdul Azeem and I came up with an algorithm to solve the problem. The code will not be shared on account of confidentiality, however, you, the reader, might as well be able to figure out the code as we go ahead and explain our approach to a given problem.