A generalized TODIM-ELECTRE II based integrated decision-making framework for technology selection of energy conservation and emission reduction with unknown weight information

Energy conservation and emission reduction (ECER) has become an indispensable trend of green life. How to choose a suitable technology for ECER under complex decision-making scenarios has become a key issue faced by traditional industrial enterprises. In this paper, a new integrated decision-making framework is established for technology-selection problems. Firstly, to describe complex linguistic information more accurately and reduce information loss, this framework employs the double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) to describe the performance of alternatives. To avoid data redundancy and simplify the computation, we improve the operations of double hierarchy hesitant fuzzy linguistic elements (DHHFLEs) and propose a new comparison method for DHHFLEs. Secondly, based on the proposed normalized projection-based difference measurement, a novel method is proposed to derive the weights of experts regarding each criterion, the group decision-making method based on the best-worst method is also utilized to derive the criteria's weights via consistent pairwise comparisons. Further, an integrated generalized TODIM (an acronym in Portuguese of interactive and multiple attribute decision making)-ELECTRE II (Elimination and Choice Translating Reality II) method is established to rank alternatives, which has the advantages of dealing with the non-compensatory problem of criteria and considering risk-aversion behavior of experts simultaneously. Subsequently, a case study of emission-reduction technology investment is provided to manifest the practicality and reliability of the given framework. Finally, the preponderance and effectiveness of the proposed method are illuminated through a comparative analysis with several existing representative methods.

Automated summary

The paper establishes a new integrated decision-making framework for technology selection problems by utilizing double hierarchy hesitant fuzzy linguistic term sets for describing alternative performance and proposing improved operations and comparison methods for double hierarchy hesitant fuzzy linguistic elements. A novel method based on normalized projection-based difference measurement is introduced for deriving expert weights and a group decision-making method based on the best-worst method is used to derive criteria weights. An integrated generalized TODIM-ELECTRE II method is developed for ranking alternatives, addressing non-compensatory criteria and expert risk-aversion behavior. The practicality and reliability of the framework are demonstrated through a case study and comparative analysis with existing methods.