Unmanned Combat Aerial Vehicle (UCAV) cooperative task allocation under Manned Combat Aerial Vehicle’s (MCAV) limited control is one of the important problems in UCAV research field. Hereto, we analyze the key technical and tactical indices influence task allocation problem and build an appropriate model to maximize the objective function values as well as reflecting various constraints. A novel improved multigroup ant colony algorithm (IMGACA) is proposed to solve the model; the algorithm mainly includes random sequence-based UCAV selection strategy, constraint-based candidate task generation strategy, objective function value-based state transition strategy, and crossover operator-based local search strategy. Simulation results show that the built model is reasonable and the proposed algorithm performs well in feasibility, timeliness, and stability.
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