CAJ | 학술논문

针对多目标粒子群算法多样,不好、收敛精度不高等问题，提出了一种改进的多目标粒子群优化算法。该算法设计了一种基于聚类算法的全局引导策略，并对初始惯,权值进行了非线,递减的自适应调整。结合现阶段我军弹药维修任务调配中的实际问题，构建了弹药维修任务调配多目标优化模型。通过算例求解和 MATLAB 仿真，验证了该算法的 Pareto 解集具有更好的多样,和收敛,，为我军弹药维修的定量决策提供了参考。
침대다목표입자군산법다양,불호、수렴정도불고등문제，제출료일충개진적다목표입자군우화산법。해산법설계료일충기우취류산법적전국인도책략，병대초시관,권치진행료비선,체감적자괄응조정。결합현계단아군탄약유수임무조배중적실제문제，구건료탄약유수임무조배다목표우화모형。통과산례구해화 MATLAB 방진，험증료해산법적 Pareto 해집구유경호적다양,화수렴,，위아군탄약유수적정량결책제공료삼고。
An improved method is proposed against the shortcomings of poor diversity and weak conver-gence accuracy in multi-objective particle swarm optimization algorithm.The algorithm devises a global guidance selection strategy based on clustering algorithm and makes self-adaption of inertia weight non-linear decreasing.The multi-objective optimization model of ammunition maintenance task allocation is built according to the problems of army ammunition maintenance task allocation.Through examples solu-tion and MATLAB simulation,it is proved that the improved algorithm has a better diversity and conver-gence in the Pareto solution set,which provides references for quantitative decisions of army ammunition maintenance.