A Z-number-based three-way decision method with classification-based state determination for the evaluation of new energy enterprises

Abstract

New energy enterprises are important promoting factors for sustainable development of modern society. Limited budgets of governments require that new energy enterprises should be efficiently evaluated before they are founded. Existing evaluation methods ignored the hesitation of experts to some alternatives. Although the three-way decision method has been applied widely as a method to evaluate alternatives, the determination of the state set has not been deeply discussed. To solve these challenges, this paper proposes a Z-number-based three-way decision method with classification-based state determination, which can assign alternatives with hesitation to a boundary region for further consideration and compute the conditional probability with a classification-based method. First, since traditional fuzzy sets cannot ensure the reliability of decision information, an evaluation matrix based on Z-numbers is constructed. Second, a fuzzy best-worst method is applied to determine the weights of criteria. Third, the conditional probability is computed based on classification-based state sets that are obtained by a sorting method. An example regarding the evaluation and selection of new energy enterprises demonstrates the validity and stability of the proposed method. The comparison analysis shows that our proposed method can divide alternatives into different regions efficiently and is less affected by the variation of parameters.