The embodiments of the present invention provide a multi-station multi-unmanned-aerial-vehicle task allocation and flight path planning method and a multi-station multi-unmanned-aerial-vehicle task allocation and flight path planning system. The multi-station multi-unmanned-aerial-vehicle task allocation and flight path planning method comprises: according to known battlefield information, allocating weapons to each combat target point by using weapon configuration and allocation strategy; allocating the target points to a plurality of stations according to target clustering strategy, and combining each station and the combat target point allocated to the station into an area so as to obtain a plurality of areas; according to area full loop generation strategy, generating initial combat full loops of each area; according to area full loop dividing strategy, dividing the initial combat full loops in each area into a plurality of sub loop combat sequences executed by a plurality of single unmanned aerial vehicles, wherein the set of the sub loop combat sequences of the plurality of the areas is the initial feasible solution of a multi-station multi-unmanned-aerial-vehicle task allocation and flight path; and obtaining the optimized final solution by carrying out evolutionary learning on the initial feasible solution, and rapidly obtaining the optimized multi-station multi-unmanned-aerial-vehicle task allocation and flight path planning scheme.