复杂人力资源约束下的抢占式维修工序调度

Preemptive maintenance process scheduling under complex humanresource constraints

针对维修保障系统内部工序调度问题具有工序多、维修人员种类不同、维修人员等级不同等复杂特性,建立以维修工时最短和人力资源总负荷最小为目标函数的多目标多约束优化模型,设计了基于关键路径算法的优先权值编码对抢占式调度问题进行第一层编码,采用随机产生方案得出第二层人力资源编码,进而针对混合粒子群遗传算法设计符合抢占式调度的交叉算子,利用Matlab软件对实例分别进行无抢占、一次抢占、多次抢占调度方案仿真,最后对仿真结果进行对比分析.仿真结果得出了多工序在多工种和多等级人力资源约束下的多次抢占式维修工序调度方案,以及无抢占、一次抢占、多次抢占调度所对应的目标函数解,决策者可根据实际需求设定目标函数权值以得出最佳调度方案.

In view of the complex characteristics of the internal process scheduling problem of the maintenance support system,such as multiple processes,different types of maintenance personnel,and different levels of maintenance personnel,this paper establishes a multi-objective and multi-constraint optimization model with the shortest maintenance man-hour and the minimum total human resource load as the objective function.The priority value encoding based on the critical path algorithm is used to code the preemptive scheduling problem at the first level,and the second level human resource code is obtained by using a random generation scheme,and then a crossover algorithm that meets the preemptive scheduling is designed for the hybrid particle swarm genetic algorithm.We use Matlab software to simulate the examples of non-preemption,one-time preemption,and multiple preemption scheduling schemes respectively,and finally compare and analyze the simulation results,through which we obtain a multi-process preemptive maintenance process scheduling scheme under the constraints of multi-work and multi-level human resources,as well as the objective function solution corresponding to the scheduling of no preemption,one preemption,and multiple preemption.Decision makers can set the weight of the objective function according to actual needs to get the best scheduling plan.