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Path planning of multiple unmanned aerial vehicles (UAVs) is a crucial step in cooperative operation of multiple UAVs, whose main difficulties lie in the severe coupling of time and three-Dimensional (3D) space as well as the complexity of multi-objective optimization. For this purpose, the time stamp segmentation (TSS) model is first adopted to resolve the timespace coupling among multiple UAVs. Meanwhile, the solution space is reduced by transforming the multiobjective problem to a multi-constraint problem. In consequence, based on the elite retention strategy, a novel improved fruit fly optimization algorithm (NIFOA) is proposed for multi-UAV cooperative path planning, which overcomes the shortcomings of basic fruit fly optimization algorithm in slow convergence speed and the potentials to fall into local optima. In particular, the multi-subpopulations evolution mechanism is further designed to optimize the elite subpopulation. At last, the effectiveness of the proposed NIFOA has been verified by numerical experiments.

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