An integrated approach of fuzzy risk assessment model and data envelopment analysis for route selection in multimodal transportation networks

Abstract

The main objective of this study is to first propose a novel integrated framework of fuzzy risk assessment model (FRAM), data envelopment analysis (DEA), and multiple criteria decision-making (MCDM) approaches for route selection in multimodal transportation networks. In the FRAM phase, the magnitude calculation of risks was operated by decision makers, who can provide their opinions on the probability of occurrence and severity of consequences through linguistic variables and triangular fuzzy numbers for risk likelihood and severity scales. The Mamdani fuzzy rule-based inference system including the rule’s firing strengths is established to convert the membership degrees for each term of aggregated likelihood and severity scales into those for each term of the risk magnitude scale. In the DEA phase, precise and crisp risk magnitudes are characterized by a new defuzzifier based on the DEA algorithm, which is applied instead of classical defuzzification methods. The three decision criteria of transportation cost, transportation time, and overall risk magnitude are weighted by a fuzzy analytic hierarchy process and then investigated based on the consensus of decision makers’ needs by a zero-one goal programming model, which is used to select the most appropriate multimodal route. Finally, the integrated approach is tested to reveal its capability and aptness using a real-world multimodal freight transportation route selection between Thailand and Cambodia. The proposed framework contributes to an easy-to-apply technique for risk predictability in multimodal transportation networks and provides powerful decision-making for the effective selection of the most appropriate alternative under the fuzzy context.