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文摘针对不确定环境下超视距空战中多架先进四代机协同攻击多个空中敌对目标的问题进行了研究。首先,构建空战态势评估指标体系,并用区间层次分析法(IAHP)和模糊优选法确定指标的主客观权重。然后建立相应的不确定环境下的多目标优化攻击效能评估模型,将协同多目标攻击决策问题转化为导弹攻击配对优化问题。进一步提出一种基于区间灰数的模拟退火遗传算法(ISAGA)用于该决策问题的求解,针对性地设计了新的选择操作和相应的模拟退火机制,有效防止算法过早陷入局部最优并能在有限迭代次数内得到满意的解。最后根据寻优所得的解确定合理的攻击方案。仿真结果表明所提出的算法能有效解决不确定环境下协同多目标攻击决策问题。
Abstract Aiming at the problem that multiple advanced four generations of machines cooperate to attack a number of aerial hostile targets in over-the-horizon air combat in uncertain environment, First, the evaluation index system of air combat situation is constructed, and the subjective and objective weights of indicators are determined by the method of interval-level analysis (IAHP) and fuzzy optimization. Then, a multi-objective optimization attack effectiveness evaluation model is established under the corresponding uncertain environment, and the cooperative multi-objective attack decision-making problem is transformed into the missile attack pairing optimization problem. Furthermore, an interval gray number based Simulated Annealing Genetic Algorithm (ISAGA) is proposed to solve this decision problem. A new selection operation and corresponding simulated annealing mechanism are designed to effectively prevent the algorithm from falling into the local optimum A satisfactory solution can be obtained in a finite number of iterations. Finally, according to the optimal solution obtained to determine a reasonable attack plan. The simulation results show that the proposed algorithm can effectively solve the cooperative multi-target attack decision problem in uncertain environment.