An efficient healthcare chain design for resolving the patient scheduling problem: queuing theory and MILP-ASA optimization approach-Reference-Cited by-同舟云学术

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An efficient healthcare chain design for resolving the patient scheduling problem: queuing theory and MILP-ASA optimization approach

Published:2023-03-29 Issue:1 Volume:328 Page:3-33
ISSN:0254-5330
Container-title:Annals of Operations Research
language:en
Short-container-title:Ann Oper Res

Author:

Ala Ali,Yazdani Morteza,Ahmadi Mohsen,Poorianasab Aida,Attari Mahdi Yousefi Nejad

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,General Decision Sciences

Link

https://link.springer.com/content/pdf/10.1007/s10479-023-05287-5.pdf

Reference54 articles.

1. Abdolazimi, O., Salehi Esfandarani, M., Salehi, M., Shishebori, D., & Shakhsi-Niaei, M. (2023). Development of sustainable and resilient healthcare and non-cold pharmaceutical distribution supply chain for COVID-19 pandemic: A case study. The International Journal of Logistics Management, 34(2), 363–389.

2. Ahmadi-Javid, A., Jalali, Z., & Klassen, K. J. (2017). Outpatient appointment systems in healthcare: A review of optimization studies. European Journal of Operational Research, 258(1), 3–34.

3. Aldrighetti, R., Zennaro, I., Finco, S., & Battini, D. (2019). Healthcare supply chain simulation with disruption considerations: A case study from Northern Italy. Global Journal of Flexible Systems Management, 20(1), 81–102.

4. Almutairi, A. M., Salonitis, K., & Al-Ashaab, A. (2019). Assessing the leanness of a supply chain using multi-grade fuzzy logic: a healthcare case study. International Journal of Lean Six Sigma.

5. Bandi, C., Trichakis, N., & Vayanos, P. (2019). Robust multiclass queuing theory for wait time estimation in resource allocation systems. Management Science, 65(1), 152–187.

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