【摘要】 作战半径条件约束下,多机种协同的联合任务规划尚无较好的解决方案。研究工作建立了基于作战半径约束的平台路线模型,将联合任务分配问题进行建模,改进蚁群算法为多信息素蚁群优化(Multi-Pheromone Ant Colony Optimization)算法,为每一个平台提供一种信息素,改变蚁群的搜索策略和更新策略。仿真实验表明,对于一组任务和平台,算法可以得到有效的分配结果,与贪心策略的遗传算法相比,在任务数量较多时,算法在求解效果上有较大优势。更多还原

【Abstract】 Under the constraints of the operational radius conditions,there is no better solution for the joint mission planning of multiple models. The research established a platform route model based on the combat radius constraint,modeled the joint task assignment problem,and improved the ant colony algorithm as a multi-Pheromone Ant Colony Optimization algorithm to provide a platform for each platform.Pheromone,changing the ant colony’s search strategy and update strategy. Simulation experiments show that for a set of tasks and platforms,the algorithm can obtain effective allocation results. Compared with the genetic algorithm of greedy strategy,the algorithm has a great advantage in solving the problem when the number of tasks is large.更多还原