Approaches to the selection of cold chain logistics enterprises under hesitant fuzzy environment based on decision distance measures

Abstract

Hesitant fuzzy sets are very useful in dealing with decision making problems for imprecise information. Taking account that there exist differences among the decision information given by decision makers and the hesitant fuzzy information given is in different accurate levels, we propose the concept of accuracy weight vector based on the decision distance measures for hesitant fuzzy sets to get a more accurate result. We develop the hesitant fuzzy accurate weighted average (HFAWA) operator and the hesitant fuzzy accurate weighted geometric (HFAWG) operator, where the weights of the attributes are determined by the accurate degrees of the hesitant fuzzy information. The properties of the HFAWA operator and the HFAWG operator are investigated, respectively. Furthermore, we present new methods for the selection of cold chain logistics enterprises based on hesitant fuzzy information. Finally, an example is illustrated to show the applications of the new approaches under hesitant fuzzy environment based on decision distance measures.