不确定环境下考虑多技能人力资源的复杂产品MRO服务资源调度  

MRO service resource scheduling for complex products with multi-skill human resources under uncertain environment

作　　者：郭钧[1,2] 徐思旺 杜百岗 周圣文[1,2] GUO Jun;XU Siwang;DU Baigang;ZHOU Shengwen(School of Mechanical and Electrical Engineering,Wuhan University of Technology,Wuhan 430070,China;Hubei Provincial Digital Manufacturing Key Laboratory,Wuhan 430070,China)

机构地区：[1]武汉理工大学机电工程学院,湖北武汉430070 [2]数字制造湖北省重点实验室,湖北武汉430070

出　　处：《计算机集成制造系统》2024年第9期3244-3256,共13页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(51705386);中国国家留学基金资助项目(201606955091)。

摘　　要：针对复杂产品维护、维修、大修(MRO)服务资源调度中存在人力资源多技能异质而导致任务实际执行工期随着指派方案的不同而变化的问题,将多技能工调度与人员学习效应相结合,建立“任务技能人员”的匹配关系。以最小化服务完成时间、最小化人员冗余和最大化资源性能成本比为目标,构建资源调度时间参数不确定条件下的随机机会约束规划数学模型。并提出一种基于随机模拟、BP神经网络和改进NSGA-II的混合智能算法进行求解。通过具有不同参数特征的对比实验案例和敏感性分析,验证了所提模型和算法的有效性和适用性。There are different human resources with different skills in the service scheduling of Complex Product Maintenance,Repair and Overhaul(MRO).To solve the problem that the actual execution period of the task will change with the different assigned schemes,the matching relation of"task-skill-personnel"was established by combining multi-skill labor scheduling with personnel learning effect.A stochastic chance constrained programming mathematical model was established under uncertain resource scheduling time parameters with objectives of minimizing service time,minimizing personnel redundancy and maximizing the cost performance index of the resources.A hybrid intelligent algorithm based on stochastic simulation,BP neural network and NSGA-II was proposed to solve the problem.The effectiveness and applicability of the proposed method were verified by comparative experimental cases with different parameter characteristics and sensitivity analysis.

关 键 词：MRO服务资源调度 多技能人力资源 时间不确定性 随机机会约束 混合智能算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TB472[自动化与计算机技术—控制科学与工程]