Next-day operating room scheduling with uncertain surgery durations: Exact analysis and heuristics
European Journal of Operational Research, cilt.286, sa.1, ss.49-62, 2020 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 286 Sayı: 1
- Basım Tarihi: 2020
- Doi Numarası: 10.1016/j.ejor.2020.03.002
- Dergi Adı: European Journal of Operational Research
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Compendex, Computer & Applied Sciences, EconLit, INSPEC, Public Affairs Index, zbMATH, Civil Engineering Abstracts
- Sayfa Sayıları: ss.49-62
- Anahtar Kelimeler: Heuristics, Operating room planning, OR in health services, Scheduling, Stochastic optimization
- Boğaziçi Üniversitesi Adresli: Evet
Özet
Operating rooms are units of particular interest in hospitals as they constitute more than 40% of total expenses and revenues. Managing operating rooms is challenging due to conflicting priorities and preferences of various stakeholders and the inherent uncertainty of surgery durations. In this study, we consider the next-day scheduling problem of a hospital operating room. Given the list and the sequence of non-identical surgeries to be performed in the next day, one needs to determine the scheduled durations of surgeries where the actual duration of each surgery is uncertain. Our objective is to minimize the weighted sum of expected patient waiting times, room idle time and overtime. First, we provide a reformulation of the objective function in terms of auxiliary functions with a recursive pattern that enables exact analysis of the optimal surgery durations at the expense of high CPU time. Next, we develop and analyze simple-to-use and close-to-optimal scheduling heuristics motivated by practice, for the OR managers to deploy in the field. Our proposed hybrid heuristic attains 1.22% average performance gap and worst average optimality gap of 2.77%. Our solution is easy to implement as it does not require any advanced optimization tool, which is the reality of many operating room environments.