Abstract:

In order to solve the problem that several equipment detect multi-target in antimissile early warning campaign, the task decomposition strategy based on the endpoint is proposed, which is according to the characteristics of resource scheduling for antimissile early warning. A multi-objective optimization model is established based on this task decomposition strategy, and the objective of this model includes scheduling benefit, handover times and resource loading degree. By redesigning the particle encoding mode and redefinition the position updating formula in particle swarm optimization, the algorithm is suitable for solving the discrete optimization problem. Aiming at the problem of premature, a modified algorithm combining the particle swarm optimization-variable neighborhood search is presented. The experimental results show that this algorithm can resolve the problem of resource scheduling for antimissile early warning rapidly and effectively, and it has good application value.