工作流程中人员合作任务的调度优化模型仿真  

Simulation on Scheduling Optimization Model for People Cooperation Tasks in Workflow

作　　者：徐焕[1] 查志勇[2] 彭祥礼[3] 刘芬[3] 

机构地区：[1]武汉大学计算机学院,湖北武汉430060 [2]华中科技大学计算机学院,湖北武汉430060 [3]湖北省电力公司信息通信公司,湖北武汉430060

出　　处：《计算机仿真》2014年第12期380-383,396,共5页Computer Simulation

摘　　要：多人合作的大型工作任务进行调度,可以极大提高工作效率。大型企业的工作任务往往需要由多人次反复合作完成。人员之间的工作流程本身充满了利益矛盾,且矛盾呈现多维度,多链条的关系。传统的调度算法都是以单线路、单个人员的工作任务最优为目标,应用到多人次的过程中时,会由于矛盾过多,使模型不收敛,容易造成调度效率低,人力资源调配不合理。提出采用改进粒子群算法的工作流程中多人员合作任务的调度优化模型。对多人次、多任务建立优化目标,根据粒子群间的协作,对多人次调度过程进行求解,求得的接运用校验过程进行最优化试错,根据最终结果获取调度模型的最优解,得到工作流程中人员合作任务的最佳调度方法。实验结果表明,利用改进粒子群算法进行工作流程中人员合作任务调度优化处理,能够提高调度效率,提高资源利用率。The large -scale tasks scheduling of multi -people cooperation can greatly improve work efficiency. Large - scale companies are often required to complete the task by a number of people with repeated cooperation. Work flow itself between peoples is full of conflicts of interest, which presents multi - dimensional and multi - chain relationships. A scheduling optimization model for multi - people collaboration of workflow was proposed based on an improved particle swarm algorithm. The optimization objectives were established by multi - people and multi - tas- king. Based on collaborations among particle swarms, the scheduling process of collaborative was solved. This result was verified by the verification process to get the optimized results of the scheduling model and the best workflow task scheduling method for personnel cooperation. The experimental results show that when the improved particle swarm is applied to the optimization scheduling of personnel cooperation of workflow,it can improve scheduling efficiency and resource utilization.

关 键 词：合作任务 调度 粒子群算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]