步入式多阶段患者流程调度：基于DES评估的ASP模型
Walk-In Multi-Stage Patient Flow Scheduling: An ASP Model with DES-Based Evaluation
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中文总结 AI 辅助
针对多科室医院步入式患者的流程调度问题，提出基于Answer Set Programming (ASP) 结合clingo的建模方法，优化两部分成本，并通过离散事件模拟 (DES) 评估。相比基于DES的基线，该方法减少了患者中位停留时间，增加了零等待患者比例。
中文摘要 AI 辅助
有效的患者检查和测试时间表在医院资源管理中起着关键作用。本文针对多科室医院中随时间到达且每次就诊需多次检查的步入式患者，制定了一个新的反应式患者流程调度问题。调度器在患者到达时为其计算可行的检查路径，包括检查顺序和房间分配，同时先前安排保持不变，该过程受医疗优先级约束和房间容量限制。我们用Answer Set Programming (ASP) 结合clingo对问题进行声明式建模，并优化两部分成本。为评估随机服务时间下的鲁棒性，提出离散事件模拟 (DES) 评估层和基线贪婪策略进行比较。在各种容量和患者负荷的大规模合成数据集上，ASP方法与基于DES的基线相比，减少了中位停留时间，增加了零等待患者的比例。这些改进在重负荷下最为明显，且在所有容量设置下均优于基线，高容量时收益较小。
英文摘要
An effective examination and test schedule for patients plays a crucial role in hospital resource management. In this work, we formulate a new reactive patient-flow scheduling problem in multi-department hospitals where walk-in patients arrive over time and each patient requires multiple examinations per visit. Upon each arrival, the scheduler computes a feasible examination pathway-both the sequence of examinations and the room assignment-for the incoming patient only, while previously scheduled assignments remain fixed. This process is subject to medical precedence constraints and room capacity limitations. We model the problem declaratively in Answer Set Programming (ASP) with clingo, and optimize a two-part cost: travel time between consecutive examination locations and queue-induced waiting time, weighted by the duration of the upcoming examination. To assess robustness under stochastic service times, we propose a Discrete-Event Simulation (DES) evaluation layer and a baseline greedy policy for comparison. On large-scale synthetic datasets across various capacity regimes and patient loads, the ASP approach reduces median stay time and increases the proportion of zero-wait patients compared to DES-based baselines. These improvements are most pronounced under heavy load, while the approach still outperforms baselines across all capacity settings, with smaller gains at higher capacities.
