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The paper proposes a hybrid model, FAHP-MABAC. The fuzzyficated Saaty's scale with the AHP method (FAHP) is used for defining the weight coefficients of criteria. The MABAC method is applied in evaluating and ranking the alternatives. This hybrid model is developed in order to support decision making while selecting locations for the preparation of laying-up positions (facilities intended for concealment, protection and maneuvering of military ships).

A decision making procedure for selection of a weapon system involves different, often contradictory criteriaand reaching decisions under conditions of uncertainty. This paper proposes a novel multi-criteria methodology based on D numbers which enables efficient analysis of the information used for decision making. The proposed methodology has been developed in order to enable selection of an efficient weapon system under conditions when a large number of hierarchically structured evaluation criteria has to be processed. A novel D number based Level Based Weight Assessment – Multi Attributive Border Approximation area Comparison (D LBWA-MABAC) model is used for selection of an automatic cannon for integration into combat vehicles. Criteria weights are determined based on the improved LBWA-D model. The traditional MABAC method has been further developed by integration of interval numbers. A hybrid D LBWA-MABAC framework is used for evaluation of an automatic cannon for integration into combat vehicles. Nine weapon systems used worldwide have been ranked in this paper. This multicriteria approach allows decision makers to assess options objectively and reach a rational decision regarding the selection of an optimal weapon system. Validation of the proposed methodology is performed through sensitivity analysis which studies how changes in the weights of the best criterion and the elasticity coefficient affect the ranking results.

Level-based weight assessment (LBWA) model is a recently introduced algorithm for determining criteria weights for multi-criteria group decision making. In this paper, the authors aim to extend the basic framework of LBWA in the picture fuzzy (PF) environment using actual score (AS) measures of the picture fuzzy numbers (PFN). They apply this extended framework in addressing a real-life problem pertaining to social entrepreneurship or social entrepreneurs (SE) in the context of COVID-19. They endeavor to identify the critical challenging factors of SE in the new normal. They list the challenges as revealed through literature review and take the opinion of a group of SEs using PF linguistic scale. They then apply the proposed framework, actual score-based picture fuzzy LBWA. They notice that ability to withstand disruption risk and show resilience and fund availability and creation of a supporting business ecosystems are the major challenges that SEs face in the new normal. They carry out validity checking and sensitivity analysis, which show reasonable consistency and stability in the result.