基于QABC-IFMADM算法的有人/无人机编队作战威胁评估

信息化条件下有人/无人机编队作战环境具有高度不确定性，如何对目标进行快速有效的威胁评估成为亟待解决的问题.在直觉模糊集框架下，研究决策者对方案具有偏好，目标属性值为区间数且权重未知的评估问题，提出一种量子蜂群（QABC）优化属性权重的直觉模糊多属性决策（IFMADM）的威胁评估方法.首先，建立方案偏好模型；其次，综合考虑客观优化排序和决策者方案偏好信息，建立主客观最优属性权重优化模型，并采用量子蜂群算法优化属性权重，使得属性权重更准确地反映实际情况.最后，通过编队对地作战威胁评估算例验证了所提方法的合理性与有效性.

Threat Assessment of Manned/Unmanned Aerial Vehicle Formation Based on QABC-IFMADM Algorithm

Under the condition of information technology,there is a high degree of uncertainty in the combat environment of manned/unmanned aerial vehicle formation;so how to evaluate the threat of targets quickly and efficiently becomes an urgent problem to be solved.In the framework of intuitionistic fuzzy sets,researching the satiation that decision makers with preference information on alternatives,the target attribute value is interval number and weight is unknown,a threat assessment method with unknown attribute weight optimized by QABC (Quantum Artificial Bee Colony) optimization algorithm is proposed based on IFMADM (Intuitionistic Fuzzy Multi-Attribute Decision Making).Firstly,preference model is constructed;secondly,the optimization model of optimal attribute weights is established considering the objective optimization taxis and preference information of decision maker synthetically,making attribute weights more reasonably reflect the actual situation by QABC optimization algorithm.Finally,the effectiveness of the proposed method is demonstrated by an example of formation threat to ground attack.