多人协同舰船维修任务分配研究  

Research on Task Assignment of Ship Maintenance with Multi-person Cooperation

作　　者：杜度 李阳 李方正 易朋兴[2] 黄俊杰[2] Du Du;Li Yang;Li Fangzheng;Yi Pengxing;Huang Junjie(Unit 92578 of PLA,Beijing 100161,China;School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]中国人民解放军92578部队,北京100161 [2]华中科技大学机械科学与工程学院,武汉430074

出　　处：《机电工程技术》2023年第6期86-90,共5页Mechanical & Electrical Engineering Technology

摘　　要：舰船是一个复杂装备,其维修任务中所涉及的维修工具种类繁多,涉及的维修零部件结构复杂,维修过程需要多个维修人员执行,若没有进行合理的维修任务分配,将会造成维修现场无序和混乱的现象,进而影响舰船维修任务进程。针对上述问题,根据实际舰船维修任务分配,以不同任务之间的约束关系,建立问题描述的数学模型。考虑到粒子群算法容易陷入局部最优的问题,以粒子群算法为基础,引入遗传算法的交叉和变异操作,用遗传算法的全局搜索能力来避免陷入局部最优问题,用粒子群算法快速收敛的特性提高遗传算法的收敛速度,从而对粒子群算法进行改进。以某舰船传动装置维修为例进行了15次测试实验,结果表明,改进粒子群算法平均最优适应度为61.78,相较于粒子群算法的63.23,改进粒子群算法能够获得更优的计算结果。提出的方法在解决维修任务分配问题方面更加合理有效。Ship is complex equipment,and its maintenance tasks involve a wide variety of maintenance tools and complex structures of maintenance components.The maintenance process requires multiple maintenance personnel to execute.If there is no reasonable allocation of maintenance tasks,it will cause disorder and chaos in the maintenance site,thereby affecting the progress of ship maintenance tasks.Aiming at the above problems,according to the actual ship maintenance task assignment problem,the mathematical model of problem description is established based on the constraint relationship among different tasks.Considering that the particle swarm algorithm easy to fall into local optimum problem,based on particle swarm optimization algorithm and introduce the crossover and mutation operators of genetic algorithm,using the global search ability of genetic algorithm to avoid falling into local optimum problem,with fast convergence characteristics of particle swarm optimization algorithm to improve the convergence speed of genetic algorithm,thus to improve the particle swarm algorithm.Taking the maintenance of a warship transmission as an example,15 test experiments are carried out.The results show that the average optimal fitness of the improved particle swarm optimization algorithm is 61.78,which is better than the 63.23 of the particle swarm optimization algorithm.The proposed method is more reasonable and effective in solving the problem of maintenance task allocation.

关 键 词：舰船维修 任务分配 多人协同 粒子群算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]