This paper develops a novel optimization method oriented to the resilience of multiple Unmanned Aerial Vehicle(multi-UAV)formations to achieve rapid and accurate reconfiguration under random attacks.First,a resilience metric is applied to reflect the effect and rapidity of multi-UAV formation resisting random attacks.Second,an optimization model based on a param-eter optimization problem to maximize the system resilience is established.Third,an Adaptive Learning-based Pigeon-Inspired Optimization(ALPIO)algorithm is designed to optimize the resi-lience value.Finally,typical formation topologies with six UAVs are investigated as a case study to verify the proposed approach.The experimental results indicate that the proposed scheme can achieve resilience optimization for a multi-UAV formation reconfiguration by increasing the system resilience values to 97.53％and 81.4％after random attacks.