A novel intuitionistic fuzzy goal programming method for heterogeneous MADM with application to regional green manufacturing level evaluation under multi-source information

The existed regional green manufacturing level assessment methods pay little attention to the multi-source information such as the expert's psychological preference information, the preference information among regions, the heterogeneous information of regions on attributes and the interactions information between attributes at the same time, which is as a heterogeneous multi-attribute decision making (MADM) problems. A novel intuitionistic fuzzy goal programming is proposed for HMADM problems under multi-source information. The Choquet integral-based relative ratio is proposed on the basis of the Choquet integral measure. It is far away from the negative-ideal solution (NIS) and closeness to the positive-ideal solution (NIS) simultaneously with the interactions between attributes. Hereby the consistency and inconsistency indices with expert's hesitation degrees are defined, the attribute weights are solved by using the developed intuitionistic fuzzy goal programming models with the optimistic, pessimistic and mixed methods. The Choquet integral-based relative ratios of alternatives can be calculated to generate their ranking orders. Finally, a regional green manufacturing level assessment example and compared with existed methods show that the superiority and validity of the proposed method, which improves the intuitionistic fuzzy goal programming methods, LINMAP methods and MADM methods with the interactions between attributes.

Automated summary

This paper proposes a new method for regional green manufacturing level assessment, which takes into account the interactions between various sources of information and expert preference information. By defining consistency and inconsistency indices as well as attribute weights, the problem of multi-attribute decision making is successfully addressed.