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

In: AI, Society and Digital Transformation

Author

Listed:
  • 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)

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.

Suggested Citation

  • Mengbo Zhai & Yan Qiao & Lun Ran & Yunkai Zhai, 2026. "Static vs. Dynamic Scheduling in Teleconsultation Systems: Managing Uncertainty and Walk-Ins in Teleconsultation," Lecture Notes in Operations Research, in: Xiaolei Xie & Kejia Hu & Guiping Hu & Weiwei Chen & Robin Qiu (ed.), AI, Society and Digital Transformation, pages 126-142, Springer.
    • Handle: RePEc:spr:lnopch:978-3-032-13116-4_11
    DOI: 10.1007/978-3-032-13116-4_11
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