Fighter optimal selection based on sequential multi-criteria decision-making with uncertainty measurement

Rapid and comprehensive fighter optimisation is an important part of modern combat decision-making. However, due to the numerous influencing factors, it is difficult for decision-makers to consider comprehensively and specify the optimal decision, and it is highly subjective, which leads to different decision conclusions from person to person. Therefore, to solve the above deficiencies in fighter selection, this paper proposes a sequential decision-making framework that comprehensively considers the effectiveness, maintenance, support capability and health status of the fighter aircraft. Based on the multi-dimensional state, it provides comprehensive and credible auxiliary support for commanders. The sequential decision-making framework (called GRA-VIKOR-IFNs) uses the combination of equation and fuzzy multi-criteria decision-making (FMCDM) to evaluate the effectiveness, support capability and health in turn, to complete the step-by-step selection of fighter models, troops and sorties. The evaluation equation is for the effectiveness evaluation and a hybrid method using the extended grey correlation analysis (GRA) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method based on intuitionistic fuzzy numbers (IFNs) is for the support capability and health evaluation. The proposed strategy is in line with the logic and demand of actual combat and training decision-making and takes into account the influence of uncertain factors. Finally, a comparison with some classical methods is carried out, such as the full consistency method (FUCOM), the technique for order of preference by similarity to ideal solution (TOPSIS) and so on. The GRA-VIKOR-IFNs method is consistent with the results of other methods and the result sort resolution is 0.0619 and at least 40% higher than other methods, which can lead the commanders to a more reliable and clear decision.