A threat assessment method of group targets based on interval-valued intuitionistic fuzzy multi-attribute group decision-making

Group target (GT) is consisted of multi-class weapons that can collaboratively work and it is a basic application unit in the information warfare. Assessing the threat of GT is required for the optimal decision of troop deployment. However, it is difficult to obtain a reasonable and effective threat assessment result of GT due to the uncertain battlefield information and different judgments from various decision makers (DMs). The study aims to investigate the multi-attribute group decision-making (MAGDM) method for solving the interval-valued intuitionistic fuzzy threat assessment problem of GTs without known attribute weights and DM’s preference weights. Based on the assessment information of DMs, attribute weights are determined with the interval-valued intuitionistic fuzzy entropy. To derive the DM’s preference weights objectively, we construct a nonlinear optimization model to minimize decision makers’ overall decision-making conflict. Moreover, the artificial bee colony algorithm is introduced to solve the nonlinear constrained optimization problem in the optimization model. The decision information of multi-DM is aggregated by the interval-valued intuitionistic fuzzy weighted averaging operator (IVIFWA) with the DMs’ preference weights. In order to describe the attribute closeness degree to the ideal solution, the decision-making judgment matrix is constructed according to the ideal solution closeness degree of each GT’s attribute calculated with the cross-entropy distance. Subsequently, based on the decision-making judgment matrix, the threat degree is calculated according to the weighted average method with the attribute weights. Finally, a case of the threat assessment of group targets is provided to illustrate the implementation process and applicability of the method proposed in this paper.