基于改进粒子群算法的多席位协同任务规划

Multi-seats Collaborative Task Planning Based on Improved Particle Swarm Optimization

针对指挥控制方舱多席位协同任务规划中的任务与号手分配冲突问题,提出了一种基于改进粒子群算法的多席位协同任务规划方法。该方法对多席位协同任务进行描述和分析,建立了基于任务排序的解空间模型。在求解模型时,运用粒子群优化算法,采用多维异步处理及修正惯性权重参数对粒子群优化算法进行了改进,提高了算法的效率及局部搜索能力。实例分析表明:该模型及提出的算法能有效的减少多席位协同任务的执行时间,对指挥控制舱多席位协同任务规划具有一定的参考价值,对提高作战效率具有重要意义。

Aiming at the allocation conflict between task and operator of multi-seats collaborative task planning in command and control cabin,a multi-seats collaborative task planning method based on improved particle swarm optimization is proposed.This method describes and analyzes the multi-seats collaborative task and establishes a solution space model based on task sequence.In solving the model,the particle swarm optimization(PSO)was improved by using multi-dimensional asynchronous processing and modifying inertia weight parameters so that the efficiency and local searching ability of the PSO were improved.The example analysis shows that the model and the algorithm can effectively reduce the execution time of multi-seats collaborative task,which has certain reference value for the multi-seats collaborative task planning in the command and control cabin,and is of great significance for improving the efficiency in combat.