Navigating a transportation system challenge with hybrid fuzzy stochastic multi-choice travel time and reliability: an application to maritime transportation

In a transportation network, a diverse range of carriers, time alternatives, and cost options lead to the emergence of multi-choice parameters. Moreover, the uncertain nature and the interplay of these factors exacerbate the complexity of decision-making processes in transportation planning. Transportation in an uncertain environment requires flexibility and the ability to adapt quickly. Transportation systems capable of adjusting to diverse conditions can effectively deal with challenges and achieve optimal performance.this paper investigates a time-reliability two-objective uncertain multi-choice scenario for the transportation problem in a multi-commodity network. The proposed Multi-Commodity Network Flow (MCNF) problem has a fractional objective function with multi-choice, fuzzy random, and fuzzy variables. The probability-possibility approach handles the uncertainty and the Lagrange interpolating polynomial represents the relationship between alternative choices. The Charnes–Cooper variable transformation method converts the fractional problem into its deterministic equivalent form. A real-world example of general cargo shipment services is used to assess the model's effectiveness.