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In multiobjective air attacking tasks, it is essential to find the optimal combat preplanning for the attacking flight. This paper solves the planning problem by decomposing it into two subproblems: attacking sequence planning and attacking direction planning. According to this decomposition, we propose the VGHPSO (Variable Granularity Hybrid Particle Swarm Optimization) method. VGHPSO employs the Particle Swarm Optimization, a metaheuristic global optimization method, to solve the planning problem in multiple granularities, including optimizing the high-level attacking sequence and optimizing the low-level attacking directions for engagements. Furthermore, VGHPSO utilizes infeasible individuals in the swarm in order to enhance the capability of searching in the boundary of the feasible solution space. Simulation results show that the proposed model is feasible in the combat, and the VGHPSO method is efficient to complete the preplanning process

Sequence and Direction Planning of Multiobjective Attack in Virtual Navigation Based on Variable Granularity Optimization Method