Railway Transportation Scheme Selection Based a CODAS-COPRAS Method in Triangular Dense Fuzzy Linguistic Term Lock Environment

In the environment of global warming, it is very important to choose rail transport solutions with the lowest possible CO₂ emissions, taking into account economic, technical and safety factors. As an important part of the modern transportation system, railway transportation appears in most transportation scenarios. Therefore, choosing an eco-friendly railway transport selection scheme is conducive to further reducing pollution emissions and preventing the further deterioration of the ecological environment. Triangular Dense Fuzzy Linguistic Term Lock Set (TDFLTS) is a tool for describing uncertain information. CODAS-COPRAS is a method to solve the multi-attribute group decision-making problem. This paper first introduces TDFLTS to describe uncertain information. Secondly, the distance measure and similarity measure between TDFLTS are proposed. Then, MEREC and DEMATEL methods are used to obtain attribute weights. Finally, CODAS-COPRAS method is used to solve the multi-attribute decision-making problem under TDFLTS environment, and it is applied to the research of railway transportation scheme selection.