Neutrosophic Sets and Systems
Abstract
The A* search algorithm is widely utilized to evaluate the shortest path in a given network. However, in a traditional A* search algorithm, the nodes are assumed to have crisp values, i.e., a single value. This assumption may not hold in many real-world scenarios where uncertainty or ambiguity is involved. In such cases, an interval-valued Neutrosophic Pythagorean (IVNP) environment can provide a more sound and accurate representation. Interval-valued Neutrosophic Pythagorean sets (IVNPS) are an effective way to model vague and imprecise data, which is prevalent in executive problems. These sets provide a more flexible way to capture uncertainty by allowing the values of nodes in the graph to vary within certain intervals rather than having fixed values. This interval representation can effectively handle imprecise or incomplete information and is a powerful tool in executive processes. In this research paper, we proposed an improved A* search algorithm that takes advantage of the interval-valued neutrosophic Pythagorean environment. This algorithm aims to evaluate the shortest path in a graph under uncertainty and ambiguity. The proposed algorithm incorporates the IVNPS theory into the A* search framework to handle the uncertainty in node values and edge weights. It utilizes the concept of neutrosophic Pythagorean distance to calculate the heuristic function and make informed decisions on the next node to expand.
Recommended Citation
Raut, Prasanta Kumar; Sakya Singh Satapathy; Siva Prasad Behera; Said Broumi; and Ajay Kumar Sahoo. "Solving the shortest path Problem in an interval-valued Neutrosophic Pythagorean environment using an enhanced A* search algorithm." Neutrosophic Sets and Systems 76, 1 (2025). https://digitalrepository.unm.edu/nss_journal/vol76/iss1/20
