为提高卫星星座网络受到攻击后的抗毁性及工作能力，提出了一种模拟退火狼群算法。该算法利用主客观权重法结合综合逼近理想排序法(TOPSIS:Technique for Order Preference by Similarity to Ideal Solution)对网络中的节点进行重要度评估，并按照节点重要度排序依次攻击。以网络连通度与网络连通效率为优化目标，卫星星座网络通信限制为约束条件，采用运动算子的思想实现狼群自适应步长的游走、召唤和围攻。使用通过优化得出的加边方案对网络结构进行优化。实验表明，与其他优化算法相比，该算法具有优越性，解决了卫星星座网络在受到攻击后工作能力下降的问题，提高了其受到攻击后的抗毁性。
Optimization of Constellation Invulnerability Based on Wolf Colony Algorithm of Simulated Annealing Optimization
In order to improve the invulnerability and working ability of the satellite constellation network after being attacked,a simulated annealing wolf pack algorithm is proposed.We use the subjective and objective weight method combined with the TOPSIS(Technique for Order Preference by Similarity)to Ideal Solution to evaluate the importance of nodes in the network,and attack the network according to the order of node importance.The network connection efficiency is the optimization goal,and the satellite constellation network communication limitation is the constraint condition.The idea of motion operator is adopted to realize the walking,summoning and sieging of wolves with adaptive step size.The network structure is optimized using the edge-adding scheme obtained through optimization.Experiments show that compared with other optimization algorithms,this algorithm has superiority.It solves the problem that the satellite constellation network's working ability declines after being attacked,and improves its invulnerability after being attacked.
satellite networkinvulnerability optimizationsimulated annealing algorithmimproved wolf colony algorithm
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维普
