To obtain the most preferred LCTD, we present the effective MADM approach for the problem, where attribute weights are partly unknown due to the problem complexity.
As a significant part of economic development, the tourism industry is encouraging low-carbon tourism and developing low-carbon tourism destinations (LCTDs).
Next, we would like to employ an illustrative example to provide certain reference attributes for unbalanced linguistic selection of LCTDs by applying the proposed MAGDM approach.
The time-complexity of the LCTD algorithm is O([v.sup.3]logv).
In a recent study, Darbha and Agrawal  proposed a TDB scheduling algorithm using similar principles as the LCTD algorithm.
The partitioning and scheduling tool consists of the HNF algorithm, the LC algorithm, and the LCTD algorithm.