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Modified formulation for the appointment scheduling problem of outpatient chemotherapy departments

机译:门诊化疗科预约时间表的修改公式

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The problem of appointment scheduling in outpatient chemotherapy departments is a hard problem due to the fact of a large number of variables, and thus unrealistic computation times are required. In this paper, we propose a new approach inspired by the cellular manufacturing concept to reduce the number of variables and constraints in a current approach retrieved from the literature. The developed model assigns every nurse to a cluster of patients and chairs on the optimum time slot to achieve the minimum completion time of all the treatments. The modified formulation has the advantage of reducing the number of variables and constraints, and thus increases the ability to give optimal solutions for real problems in reasonable computation times. Another advantage, it dedicates a nurse for each group of patients in their whole treatment time other than assigning a nurse just to start up the treatment. Moreover, this model balances the nurse workload along the working time as much as possible. We conduct numerical experiments to highlight the computation times of the current model and the modified one and also give a benchmark analysis for a small instance. The results show that the computation times of the developed model are less than the current model. Finally, we propose a solution framework for the modified model based on clustering and mathematical programming.
机译:由于存在大量变量,因此门诊化疗科的预约安排问题是一个难题,因此需要不切实际的计算时间。在本文中,我们提出了一种受蜂窝制造概念启发的新方法,以减少从文献中检索到的当前方法中的变量和约束的数量。开发的模型在最佳时段将每位护士分配给一群病人和椅子,以实现所有治疗的最短完成时间。修改后的公式的优点是减少了变量和约束的数量,从而提高了在合理的计算时间内为实际问题提供最佳解决方案的能力。另一个优点是,它在整个治疗时间内为每组患者安排了一名护士,而不是只指派一名护士开始治疗。此外,该模型尽可能地平衡了护士在工作时间内的工作量。我们进行了数值实验,以突出显示当前模型和修改后模型的计算时间,并给出了一个小实例的基准分析。结果表明,所开发模型的计算时间少于当前模型。最后,我们提出了一种基于聚类和数学编程的改进模型的解决方案框架。

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