The outcome of a work process depends on which tasks are assigned to which employees. However, sometimes optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution. Likewise, an even workload distribution without considering the employee’s qualifications may cause unproductive employee-task matching that results in low performance. This trade-off is even more noticeable for work processes during critical time junctions, such as in military command centers and emergency rooms that require fast, effective and error free performance. This study evaluates optimizing task-employee assignments according to their capabilities while also maintaining a workload threshold. The goal is to select the employee-task assignments in order to minimize the average duration of a work process while keeping the employees under a workload threshold to prevent errors caused by overload. Due to uncertainties related with the inter-arrival time of work orders, task durations and employees’ instantaneous workload, a simulation–optimization approach is required. A discrete event human performance simulation model was used to evaluate the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search the solution space. A sample work process is used to show the effectiveness of the developed simulation–optimization approach. Numerical tests indicate that the proposed approach finds better solutions than common practices and other simulation–optimization methods. Accordingly, by using this method, organizations can increase performance, manage excess-level workloads, and generate higher satisfactory environments for employees, without modifying the structure of the process itself.

中文翻译：

---

通过任务分配和心理工作量的仿真优化来改善工作流程

工作过程的结果取决于将哪些任务分配给哪些员工。但是，有时根据员工的资格进行优化分配可能会导致工作量分配不均且效率低下。同样，不考虑员工资格的均匀工作负载分配可能会导致无效的员工任务匹配，从而导致绩效降低。这种权衡对于关键时间交界处的工作流程尤为明显，例如在军事指挥中心和急诊室等需要快速，有效和无差错性能的地方。这项研究评估了根据任务雇员的能力优化他们的能力，同时还保持了工作量阈值。目的是选择员工任务分配，以使工作流程的平均时间最少，同时使员工保持在工作负载阈值以下，以防止因过载而导致的错误。由于与工单到达时间，任务持续时间和员工的瞬时工作量相关的不确定性，因此需要一种模拟优化方法。离散事件人类绩效仿真模型用于评估问题的目标函数，并结合基于遗传算法的元启发式优化方法来搜索解决方案空间。使用示例工作过程来说明开发的仿真优化方法的有效性。数值测试表明，与常用方法和其他仿真优化方法相比，所提出的方法找到了更好的解决方案。因此，