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Affected by the rescue environment and the unmanned aerial vehicle(UAV) communication technology, communication among UAVs is greatlyrestricted. How to do rescue mission planning for UAV swarms underlimited communication has become a difficult problem. This paperproposes a motif-based mission planning model which generates amission planning strategy as a task priority execution order isinputted. The choice of mission planning strategy turns to be thechoice of a task priority execution order which is a many-objectiveoptimization problem. Permutation and combination of task priorityexecution order contribute to the generation of mass feasible task planningstrategies. The increase in the number of tasks leads to the explosionof the amount of calculation. We enhance preference-inspiredco-evolutionary algorithm with goal vectors (PICEA-g) by usingthe K-means clustering method in the step of offspring selection to selectout next-generation goal vectors. The proposed algorithm, calledk-PICEA-g is applied in the optimization processminimizing, simultaneously, the mission completion time, the total number of changed connections, and the averagenumber of used UAVs through changing the priority execution order oftasks. As an example of application, we apply the improvedPICEA-g to optimize the execution order of a set of tasks,achieving a set of non-dominated solutions from which the decisionmaker can select the most adequate one. By experiments, thefeasibility and effectiveness of this algorithm are validated.

A Motif-Based Rescue Mission Planning Method for UAV Swarms Usingan Improved PICEA