An extended VIKOR method using stochastic data and subjective judgments

Decision makers (DMs) face different levels of uncertainty throughout the decision making process. In particular, natural language is generally subjective or ambiguous when used to express perceptions and judgments. The aim of this paper is to extend the VIKOR method and develop a methodology for solving multi-criteria decision making (MCDM) problems with stochastic data. The weights of the stochastic decision criteria considered in our extended VIKOR model have been determined using the fuzzy analytic hierarchy process (AHP) method. We present a case study in the banking industry to demonstrate the applicability of the proposed method. We also compare our results with the results obtained from a stochastic version of the super-efficiency data envelopment analysis (DEA) model to exhibit the efficacy of the procedures and algorithms. 2016 Elsevier Ltd. All rights reserved.