Abstract
MAV/UAV cooperative combat mission planning: based on the integration task of reconnaissance, decision, attack and damage assessment, the heterogeneity of clusters, the limitation of airborne resources and the constraints of multitask time order are all considered. By utilizing graph theory and combinatorial optimization theory, an optimization model for MAV/UAV cooperative mission planning is established. An improved genetic algorithm is proposed to solve the problem. By designing genetic operators such as population initialization, crossover and mutation, the heterogeneity and resource limitation are successfully solved. Then an optimal solution is obtained in the process of population evolution. Finally, an example is given to prove the feasibility and effectiveness of the proposed model and method.
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