SMAA methods and their applications: a literature review and future research directions

A stochastic multicriteria acceptability analysis–evidential reasoning method for uncertain multiattribute decision‐making problems

“…The potential beneficiary of such analysis may be a customer or a third‐party assessment structure. The management decision‐making problems in many other fields are usually made under conditions of uncertainty, especially in industrial fields (Pelissari et al, ), and it is difficult for DMs from different interest groups to get uniform attribute weights (Govindan, Kadziński, Ehling, & Miebs, ; Song, Fu, Zhou, & Lai, ). Therefore, our proposed method is advantageous and applicable in industrial fields.…”

“…Depending on the DM's setting, SMAA‐2 computes the probability of each most preferred alternative by inverse exploration of the feasible weight space for full ranking (Lahdelma & Salminen, ). In recent years, SMAA‐2 and its variants have been applied to many fields, such as decision analysis (Angilella et al, ; Pelissari, Oliveira, Amor, Kandakoglu, & Helleno, ), market segmentation (Liu, Liao, Huang, & Liao, ), sustainable energy evaluation (Loikkanen, Lahdelma, & Salminen, ), and reservoir flood control operation (Zhu, Zhong, & Sun, ).…”

“…In the SMAA‐2 method, the evaluation information of each attribute is aggregated by using a multiattribute utility procedure, one of the classical approaches in UMADM. However, when a DM's preference structure does not meet the “additive independence” condition (Yang, Yang, Liu, & Li, ), or a partial missing attribute value appears in the decision matrix, the multiattribute utility function loses its usefulness (Pelissari et al, ). Instead of the multiattribute utility function, the different aggregation procedures should be applied in such a case.…”

As simple as possible but not simpler in Multiple Criteria Decision Aiding: the robust-stochastic level dependent Choquet integral approach

“…• putting together (31) and (35), we obtain 0.5 > µ L (P h, t) for all t ∈]25, 30], so that, considering also (37) and reminding that µ L ({M, P h}, t) = 1 for all t, we get µ L (P h, t) + µ L (M, t) < µ L ({M, P h}, t) for all t ∈]25, 30], confirming the synergy between Mathematics and Physics for notes greater than 25;…”

A multicriteria decision support tool for modelling bank credit ratings

“…This study complements the latter modelling framework by employing the recently introduced SMAA-Fuzzy-FlowSort (hereafter referred to as 'SMAA-FFS'; Pelissari et al 2019a), the first Stochastic Multiobjective Acceptability Analysis (SMAA) (Lahdelma et al 1998;Lahdelma and Salminen 2001) variant of PROMETHEE-based sorting 1 methods. The framework of SMAA is used as a means to deal with imperfections and uncertainty in real world applications, and it has a wide gamut of applicability that extends and crosses several disciplines (see Pelissari et al 2019b for a recent survey). Of course, turning to the case of our interest in particular, an effective credit risk assessment/modelling is well in line with the characteristics of the proposed method for a variety of reasons that we list forthwith.…”