An adjustable fuzzy chance-constrained network DEA approach with application to ranking investment firms

This paper presents a novel approach for performance appraisal and ranking of decision-making units (DMUs) with two-stage network structure in the presence imprecise vague data. In order to achieve this goal, data envelopment analysis (DEA) model, adjustable possibilistic programming (APP), chance-constrained (CCP) are applied propose new fuzzy (FNDEA) approach. The main advantages proposed FNDEA can be summarized as follows: linearity models, unique efficiency decomposing under ambiguity, capability extending other structures. Moreover, DMUs environment three stages: 1) solving model all optimistic-pessimistic viewpoints confidence levels, 2) then plotting results drawing surface scores, 3) finally calculate volume three-dimensional shape below surface. criterion. Remarkably, presented DEA is implemented investment firms (IFs) processes including operational portfolio management process. Illustrative real-life case study show that effective practically very useful.