Neutrosophic decision-making for allocations in solid transportation problems

The complexity of solid transportation problems (STP) poses a formidable challenge, driven by the intricate interplay of variables such as demand, vehicle capacity, and availability. Traditional allocation strategies frequently fail to adequately address these complexities, resulting in diminished operational efficiency. This study introduces an innovative neutrosophic decision-making framework specifically designed for STP, aiming to optimize transportation allocations by incorporating critical yet often overlooked factors like cost, time, and the reliability of conveyances. Utilizing neutrosophic sets, our methodology meticulously accounts for the inherent uncertainties in STP. This approach employs neutrosophic logic to interpret imprecise data, ensuring a comprehensive analysis. To validate the effectiveness of our proposed model, numerical computations were juxtaposed against conventional methods, revealing a significant enhancement in allocation dependability, particularly by emphasizing conveyance reliability. While our model necessitates a slight increase in costs, the improved reliability and predictiveness of allocations underscore its utility, advocating for its adoption despite the complexity it introduces. The findings indicate substantial potential for enhancing transportation reliability and efficiency, albeit with the caveat of increased model complexity and the need for detailed neutrosophic data. Future directions will focus on incorporating additional variables and leveraging advanced computational tools to expand the model's applicability and streamline computational requirements, further solidifying its position as a valuable asset in logistics.