数据驱动的业务过程角色与任务重分配方法研究

针对现有任务分配方法难以考虑人员执行任务的效率差异性和偏好性问题, 以生产和服务系统执行历史数据为基础, 提出基于人员行为差异性的任务分配方法, 建立以业务执行过程中流程执行时间最少和人员之间负荷均衡为多目标的任务分配优化模型. 基于NSGA II算法, 提出将约束优化模型转换为无约束优化模型, 并给出优化模型的求解方法. 结合业务过程挖掘领域中事件日志的应用实例, 对业务过程中的任务和角色进行重分配, 比较任务重分配前后业务过程的变化情况, 为以后的任务分配提供依据.

Data-driven task and role reassignment in business process

Existing task assignment methods are hard to consider the differences in efficiency and preference of task executive members. Based on the historical data of production and service system, the task assignment method is proposed based on the difference of staff member behavior using the task assignment optimization model which focuses on achieving the least of process execution time and the balance of the workload. Adopting the NSGAII(Non-dominated Sorting Genetic Algorithm II), the constrained optimization model is converted into unconstrained optimization model, and thus the solution of optimization model is established. Tasks and roles in the business process are reassigned in a case study extracted from an event log in mining field business. By comparing the changes of business process before and after the assignment, it is expected that the analytical results may provide supportive reference for the future task assignment.