© 2021 The Authors.Determining the shortest travel time on transportation is affected by many logistics parameters such as cost, quality, speed and satisfaction. This study proposes a new hybrid time-dependent Dijkstra’s and minimum vertex degree algorithm on a spherical bipolar fuzzy weighted graph to find shortest travel time of Hamiltonian cycles on transportation problems. To weight the transportation points in uncertain environment, decision makers can express their views with spherical bipolar fuzzy information based on the criteria. In the proposed methodology, for a given digraph, the nodes are weighted by the decision makers’ spherical bipolar fuzzy evaluations, and fuzzy Hamiltonian paths are determined using the minimum vertex degree method. The fuzzy Hamiltonian cycles constitute the routes for transportation network, and the starting point, which gives the shortest travel time, is investigated by time-dependent Dijkstra’s algorithm. This approach is an alternative way to solve the traveling salesman problem (TSP) in time-dependent graphs with Θ(VN2) time complexity. The proposed methodology is illustrated on a logistic network. It is intended to guide future graph-transportation research.
https://doi.org/10.1016/j.ifacol.2021.06.048Cite as:
@article{_akir_2021,
doi = {10.1016/j.ifacol.2021.06.048},
url = {https://doi.org/10.1016%2Fj.ifacol.2021.06.048},
year = 2021,
publisher = {Elsevier {BV}},
volume = {54},
number = {2},
pages = {348--353},
author = {Esra {c{C}}akir and Ziya Ulukan and Tankut Acarman},
title = {Shortest Fuzzy Hamiltonian Cycle on Transportation Network Using Minimum Vertex Degree and Time-dependent Dijkstra's Algorithm},
journal = {{IFAC}-{PapersOnLine}}
}