Evaluation of Shortest path on multi stage graph problem using Dynamic approach under neutrosophic environment

The shortest path problem is a classic optimization problem in graph theory and 
computer technology. It involves identifying the shortest path between two nodes 
in a graph, where each edge has a numerical weight. In this paper, we put our effort 
into examining the use of the dynamic programming method to evaluate the 
shortest path (SP) between the two specified nodes in a multistage network where 
the parameter is a multi-value neutrosophic number (MVNN). Firstly, we propose 
an algorithm based on the forward and backward approach in an uncertain 
environment and also implement our approach in the Python-3 programming 
language. Furthermore, a numerical illustration has been provided to showcase the 
effectiveness and robustness of the novel model.