Interval type-2 fuzzy programming method for risky multicriteria decision-making with heterogeneous relationship

We propose a new interval type-2 fuzzy (IT2F) programming method for risky multicriteria decision-making (MCDM) problems with IT2F truth degrees, where the criteria exhibit heterogeneous relationship and decision-makers behave according to bounded rationality. First, we develop technique calculate Banzhaf-based overall perceived utility values of alternatives based on 2-additive measures regret theory. Subsequently, considering pairwise comparisons define consistency index (BIT2FRCI) inconsistency (BIT2FRII). Next, identify optimal weights, an model is established concept that BIT2FRII must be minimized not exceed BIT2FRCI using fixed set. Furthermore, design effective algorithm external archive-based constrained state transition solve model. Accordingly, ranking order derived values. Experimental studies pertaining investment selection demonstrate state-of-the-art performance proposed method, is, its strong capability in addressing MCDM problems.