طراحی شبکه سلسله‌مراتبی مراکز درمان موقت شهری در شرایط بحران با رویکرد تلفیقی مدل ریاضی - شبیه‌سازی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی صنایع، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران.

2 دانشیار، گروه کسب و کار، دانشکده کارآفرینی، دانشگاه تهران، تهران، ایران.

3 استاد، گروه مدیریت صنعتی و فناوری اطلاعات، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران، ایران.

4 استادیار، گروه مهندسی صنایع، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات، تهران، ایران.

چکیده

اثرات ویرانگر بلایای طبیعی، اهمیت لجستیک و برنامه‌ریزی منابع انسانی را در مراحل قبل و بعد از بحران نشان می‌دهد. هنگام بروز بحران به ‌منظور امدادرسانی سریع، شبکه سلسله ‌مراتبی سلامت که شامل درمانگاه‌ها و بیمارستان‌ها است، فعال می‌شود. در این پژوهش با استفاده از مدل ریاضی مختلط عدد صحیح و با درنظرگرفتن موقعیت فعلی بیمارستان‌ها و درمانگاه‌ها، مکان‌های بهینه‌ای با عنوان «مراکز درمان موقت» تعیین و نحوه تخصیص بهینه مصدومان از ناحیه‌های شهری به این مراکز پیشنهاد می‌شود. انتخاب مکان‌های بهینه، تخصیص بهینه سلسله‌مراتبی مصدومان، تعیین ظرفیت بهینه مراکز پذیرش، تعیین نقاط پشتیبان برای مراکز درمان موقت در قالب یک مدل تلفیقی ریاضی و شبیه‌سازی به‌صورت هم‌زمان از نوآوری‌های این پژوهش است. به کمک مدل شبیه‌سازی لحظه بروز بحران و فرایند امداد و نجات شبیه‌سازی‌شده و با رویکرد بهینه‌سازی مبتنی بر شبیه‌سازی، ظرفیت بهینه مراکز موقت و اصلاح ظرفیت درمانگاه‌ها و بیمارستان‌های فعلی انجام شده است. نتایج پژوهش نشان می‌دهد مدل سلسله‌ مراتبی مکان‌یابی–تخصیص، بهینه‌سازی ظرفیت سبب کاهش ازدحام مصدومان و کاهش هزینه و زمان درمان می‌شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Designing a Hierarchical Network of Temporary Urban Medical Centers in a Disaster through a Hybrid Approach of Mathematical Model – Simulation

نویسندگان [English]

  • Sogol Mousavi 1
  • Seyed Mojtaba Sajadi 2
  • Akbar AlemTabriz 3
  • Seyed Esmaeil Najafi 4
1 Ph.D Student, Industrial Engineering Department, Islamic Azad University, Science and Research Branch, Tehran, Iran.
2 Associate Professor, Department of Business, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.
3 Professor, Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.
4 Assistant Professor, Industrial Engineering Department, Islamic Azad University, Science and Research Branch, Tehran, Iran.
چکیده [English]

The destructive impact of natural disasters emphasizes the importance of logistics and human resource planning in the pre- and post- disaster periods. In the event of a disaster, in order to provide immediate relief, the Health Hierarchical Network, which includes clinics and hospitals, will be activated. In this paper, using a mixed integer mathematical model and assuming the current location of hospitals and clinics, optimal locations are determined as temporary treatment emergency centers and the optimal allocation of casualties from urban areas to these centers and then clinics and hospitals are recommended in disaster. Using the simulation model, the moment of disaster and the rescue process were simulated and then the optimization approach was adopted based on simulating the optimal capacity of temporary centers and improving the capacity of current centers and hospitals. The results of the study show that the hierarchical model of location allocation of capacity optimization reduces the density of casualties, costs and treatment time in disaster.

کلیدواژه‌ها [English]

  • Disaster Management
  • Temporary Medical Centers
  • Simulation-based Optimization
  • Hierarchical Mathematical Model
  • Treatment Network Design

مراجع

  1. Ahmadi-Javid, A., Seyedi, P., & Syam, S. S. (2017). A survey of healthcare facility location. Computers & Operations Research, 79, 223-263.
  2. Ahmadzadeh, F., Mohammadi, N., & Babaie, M. (2019). Evaluation the Emergency Response Program of Emergency Operations Command Center of the Alborz University of Medical Sciences in Response to Kermanshah Earthquake in November 2017. Health in Emergencies and Disasters, 4(3), 135-146.
  3. Aydin, N. (2016). A stochastic mathematical model to locate field hospitals under disruption uncertainty for large-scale disaster preparedness. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 6(2), 85-102.
  4. Amiri, M., Khatami Firuozabadi, M. A., & Mobin, M. S. (2012). Emergency Medical Service Ambulance Allocation, on the Tehran-Qom Highway, using the Hypercube Queuing Model. Journal of Industrial Management Perspective, 2(3, Autumn 2012), 45-70. (In Persian)
  5. Alidost, F., Bahrami, F., & Safari. (2020). Multi-Objective Pharmaceutical Supply Chain Modeling in Disaster (Case Study: Earthquake Crisis in Tehran). Journal of Industrial Management Perspective, 3(39, Autumn 2020), 99-123. (In Persian)
  6. Beamon, B. M., & Kotleba, S. A. (2006). Inventory management support systems for emergency humanitarian relief operations in South Sudan. The International Journal of Logistics Management.
  7. Farahani, R. Z., Hekmatfar, M., Fahimnia, B., & Kazemzadeh, N. (2014). Hierarchical facility location problem: Models, classifications, techniques, and applications. Computers & Industrial Engineering, 68, 104-117.
  8. Fereiduni, M., & Shahanaghi, K. (2017). A robust optimization model for distribution and evacuation in the disaster response phase. Journal of Industrial Engineering International, 13(1), 117-141.
  9. Ghasemi, P., Khalili-Damghani, K., Hafezalkotob, A., & Raissi, S. (2020). Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake). Socio-Economic Planning Sciences, 71, 100745.

10. Gul, M., Fuat Guneri, A., & Gunal, M. M. (2020). Emergency department network under disaster conditions: The case of possible major Istanbul earthquake. Journal of the Operational Research Society, 71(5), 733-747.

11. Galindo, G., & Batta, R. (2013). Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies. Socio-Economic Planning Sciences, 47(1), 20-37.

12. Haojun, F., Jianqi, S., & Shike, H. (2011). Retrospective, analytical study of field first aid following the Wenchuan Earthquake in China. Prehospital and disaster medicine, 26(2), 130.

13. Jia, H., Ordóñez, F., & Dessouky, M. (2007). A modeling framework for facility location of medical services for large-scale emergencies. IIE transactions, 39(1), 41-55.

14. Kılcı, F., Kara, B. Y., & Bozkaya, B. (2015). Locating temporary shelter areas after an earthquake: A case for Turkey. European journal of operational research, 243(1), 323-332.

15. Kohn, S., Eaton, J. L., Feroz, S., Bainbridge, A. A., Hoolachan, J., & Barnett, D. J. (2012). Personal disaster preparedness: an integrative review of the literature. Disaster medicine and public health preparedness, 6(3), 217-231.

16. Karatas, M., & Yakıcı, E. (2019). An analysis of p-median location problem: effects of backup service level and demand assignment policy. European Journal of Operational Research, 272(1), 207-218.

17. Kamali, A, Sajjadi, S.M., & July, F. (2018). Location of medical emergency bases with the help of a combination of optimization and simulation methods (Case study: Isfahan urban emergency stations). Journal of Health Information Management, 15(2), 61 67. (In Persian)

18. Leiras, A., de Brito Jr, I., Peres, E. Q., Bertazzo, T. R., & Yoshizaki, H. T. Y. (2014). Literature review of humanitarian logistics research: trends and challenges. Journal of Humanitarian Logistics and Supply Chain Management.

19. Liu, Y., Cui, N., & Zhang, J. (2019). Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service. Transportation research part E: logistics and transportation review, 128, 1-16.

20. Manopiniwes, W., & Irohara, T. (2017). Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response. International Journal of Production Research, 55(4), 979-996.

21. Mete, H. O., & Zabinsky, Z. B. (2010). Stochastic optimization of medical supply location and distribution in disaster management. International Journal of Production Economics, 126(1), 76-84.

22. Maleki Rastaghi, M., Barzinpour, F., & Pishvaee, M. S. (2018). A multi-objective hierarchical location-allocation model for the healthcare network design considering a referral system. International Journal of Engineering, 31(2), 365-373.

23. Makui, A., Ashouri, F., & Barzinpour, F. (2019). Assignment of injuries and medical supplies in urban crisis management. Journal of Applied Research on Industrial Engineering, 6(3), 232-250.

24. Mahabadi, A., Ketabi, S., & Sajadi, S. M. (2014). Investigate the parameters which affect the patients waiting time in emergency department of orthopedic services in Ayatollah Kashani hospital with the lean management approach. 

  1. Mousazadeh, M., Torabi, S. A., Pishvaee, M. S., & Abolhassani, F. (2018). Health service network design: a robust possibilistic approach. International transactions in operational research, 25(1), 337-373.

26. Nikjoo, N., & Javadian, N. (2019). A Multi-Objective Robust Optimization Logistics Model in Times of Crisis under Uncertainty. Journal of Industrial Management Perspective, 8(4, Winter 2019), 121-147. (In Persian).

27. Oksuz, M. K., & Satoglu, S. I. (2020). A two-stage stochastic model for location planning of temporary medical centers for disaster response. International Journal of Disaster Risk Reduction, 44, 101426.

28. Paul, J. A., & MacDonald, L. (2016). Location and capacity allocations decisions to mitigate the impacts of unexpected disasters. European Journal of Operational Research, 251(1), 252-263.

29. Pouraliakbari, M., Mohammadi, M., & Mirzazadeh, A. (2017). Location of heath care facilities in competitive and user choice environment. Journal of Industrial and Systems Engineering, 10(special issue on healthcare), 24-54.

30. Rebeeh, Y. A., Pokharel, S., Abdella, G. M., & Hammuda, A. S. (2019). Disaster management in industrial areas: Perspectives, challenges and future research. Journal of Industrial Engineering and Management, 12(1), 133-153.

31. Salman, F. S., & Gül, S. (2014). Deployment of field hospitals in mass casualty incidents. Computers & industrial engineering, 74, 37-51.

32. Şahin, G., & Süral, H. (2007). A review of hierarchical facility location models. Computers & Operations Research, 34(8), 2310-2331.

33. Salehi, F., Mahootchi, M., & Husseini, S. M. M. (2019). Developing a robust stochastic model for designing a blood supply chain network in a crisis: a possible earthquake in Tehran. Annals of Operations Research, 283(1), 679-703.

34. Sepehri, Z., Arabzad, S. M., & Sajadi, S. M. (2015). Analysing the performance of emergency department by simulation: the case of Sirjan Hospital. International Journal of Services and Operations Management, 20(3), 289-301.

35. Sajadi, S. M., Ghasemi, S., & Vahdani, H. (2016). Simulation optimisation for nurse scheduling in a hospital emergency department (case study: Shahid Beheshti Hospital). International Journal of Industrial and Systems Engineering, 23(4), 405-419.

36. Salman, F. S., & Yücel, E. (2015). Emergency facility location under random network damage: Insights from the Istanbul case. Computers & Operations Research, 62, 266-281.

37. Sharma, S. D., & Tatavarthy, S. R. (2019, September). Development of optimized solution for a generic disaster management problem through construction of responsive supply chain a review. In AIP Conference Proceedings (Vol. 2148, No. 1, p. 030049). AIP Publishing LLC.

38. Shang, Q., Wang, T., & Li, J. (2020). Seismic resilience assessment of emergency departments based on the state tree method. Structural Safety, 85, 101944.

39. Toro-Díaz, H., Mayorga, M. E., Chanta, S., & McLay, L. A. (2013). Joint location and dispatching decisions for emergency medical services. Computers & Industrial Engineering, 64(4), 917-928.

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