Zero-carbon measure prioritization for sustainable freight transport using interval 2 tuple linguistic decision approaches

Abstract

Freight transport is the main source of carbon emissions. Implementing freight transport zero-carbon measures in an orderly manner has a very important practical value for sustainable development. Thus, the interval 2-tuple linguistic multi-attribute decision-making (I2TL-MADM) approach of zero-carbon measure prioritization for sustainable freight transport is presented. Considering the advantages of interval 2-tuple variables (I2TLVs) expressing the uncertainty evaluation information of zero-carbon measures, the decision model is developed based on I2TLVs. Firstly, the shortcomings of the inconsistent fuzzy preference relations (FPRs) constructed by comparing attribute values expressed by I2TLVs are revealed. Then, additive and multiplicative dominance degrees of I2TLVs are proposed, and their properties are discussed to ensure the consistency of decision information. Two I2TL-MADM methods based on the novel dominance degrees are developed to rank the zero-carbon measures of sustainable freight transport. Finally, the rationality of the developed I2TL-MADM decision framework is illustrated by numerical examples of Guangzhou. The results show that the developed decision methods can effectively construct the consistent FPRs and rank the zero-carbon measures.