A novel decision-making approach to evaluate transportation modes in a sustainable, agile and resilient supply chain network under uncertainty

One of the crucial issues in supply chains is the selection of an appropriate transportation mode for logistics operations. Various criteria and factors influence this decision, and it can vary across different supply chains. The objective of this paper is to evaluate transportation modes for the medical equipment supply chain based on sustainability, agility, and resilience criteria under uncertain conditions. Considering the significant impact of uncertainty in different scenarios, the evaluation of transportation modes needs to be conducted accordingly. Therefore, the Stochastic Fuzzy Best Worth Method (SFBWM) is utilized for this purpose and the indicators are assessed. The findings indicate that cost, speed, carrying capacity, flexibility, and national economy are the most important indicators. The main contribution of this study is the presentation of a developed approach using the Fuzzy Inference System (FIS). In this approach, the evaluation indicators are hierarchical and weighted, and the Hierarchy Weighted FIS (HWFIS) method is proposed. Based on the achieved results, agility was selected as the most important one, and sustainability and resiliency have the same rank with the same weights. Also, outputs demonstrate that the airplane is the most favorable option.