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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 55141 (01)
- University: Sharif University of Technology
- Department: Industrial Engineering
- Advisor(s): Rafiee, Majid
- Abstract:
- People's lives have been affected by the spread of the Covid-19 virus. Due to the high infectivity, governments have screened people, imposed curfews, mandated the use of masks, and so on to reduce the rate of transmission of the disease among people. Meanwhile, infected people are getting treatments: people who are slightly affected are quarantined at home, and those who are heavily affected are treated in hospitals. Hence there is an excessive increase in the hospital workload. On the one hand, this increased workload leads to physical fatigue and, on the other hand, to psychological problems, stress, etc. for the healthcare professionals. Therefore, it is very important to take care of the healthcare professionals and provide them with proper working conditions. For this reason, besides the provision of protective equipment such as gloves, overalls, mask, and glasses that are necessary for the protection of healthcare workers from the virus, healthcare services should also be planned very carefully. In this study, we schedule physicians shift during the COVID-19 virus pandemic based on their preferences. The hospital has established three new COVID-19 related. In this study, a mixed integer linear programming (MILP) model is proposed to allow physicians to have balanced shifts in the newly established COVID-19 departments in addition to service delivery in their specialty departments, taking into account preferences. This schedule allows physicians to minimize exposure to the COVID-19 virus as much as possible. Finally, by analyzing the sensitivity on the preferences parameter, there were significant changes in the results, so this parameter has a significant impact on the performance of the proposed model and its use will lead to physicians' satisfaction
- Keywords:
- Pandemic ; Mixed Integer Linear Programming ; TimeTable ; COVID-19 ; Physicians Scheduling
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