Static vs. Dynamic Scheduling in Teleconsultation Systems: Managing Uncertainty and Walk-Ins in Teleconsultation

Mengbo Zhai, Yan Qiao (), Lun Ran and Yunkai Zhai
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Mengbo Zhai: Zhengzhou University, School of Management
Yan Qiao: Zhengzhou University, School of Management
Lun Ran: Beijing Institute of Technology, School of Management and Economics
Yunkai Zhai: Zhengzhou University, School of Management

A chapter in AI, Society and Digital Transformation, 2026, pp 126-142 from Springer

Abstract: Abstract Teleconsultation in China, primarily based on appointment systems, often face walk-ins who have not scheduled in advance, leading to delays for scheduled patients. To minimize waiting and overtime costs, we propose a two-stage static scheduling model for optimal patient allocation. Additionally, a dynamic update model is developed for scheduled patients, integrated with a rolling horizon optimization strategy, resulting in a Greedy-based Rolling Horizon Optimization (GRHO) approach. We introduce two insertion principles for walk-ins: GRHO and GRHO*. The SAA-VNS-Integer L-Shaped (SVILS) algorithm is employed to solve the static model, and results show that GRHO* outperforms both GRHO and SVILS. GRHO* reduces waiting time by up to 67.86%, and increases teleconsultation room resource utilization to 89.29%, offering valuable insights for teleconsultation management.

Keywords: appointment scheduling; dynamic scheduling; rolling horizon optimization; SVILS algorithm (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-13116-4_11

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