A two-level optimization model for elective surgery scheduling with downstream capacity constraints

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

“…Constraint (8) states that the end of receiving treatment for each patient includes the time of receiving treatment in the previous stages, the time of patient preparation at that stage, the time of receiving treatment using medical equipment, and the time of receiving treatment from personnel in addition to the final condition that the patient needs services and personnel at that stage. Constraint (9) states that the end time of receiving a service for each common patient includes the time of receiving services in the previous stages (except recovery stage), the time of patient preparation at that stage, the time of receiving services from equipment, and the time of receiving services from personnel, as well as the final condition that the patient needs services and personnel at that stage. Constraint (10) indicates that the time of receiving treatment at different stages includes the patient' s preparation time, the time of providing service by medical center personnel, the duration of service, the time of entering into the system in case the given stage and ward are defined in the patient treatment description (this constraint checks if the patient needs to receive treatment at that stage, then the end time of patient process will be the sum of preparation time and receiving treatment).…”

“…Here, to verify the applicability of the proposed algorithms, the aforementioned metrics are applied to the considered test problems. These 12 test problems are divided into small-sized (1-4), medium-sized (5-8), and large-sized (9)(10)(11)(12)(13)(14)(15).…”

“…Therefore, centers is related to operating rooms [8]. It verifies the importance of operating room and its proper utilization [9,10]. The operating room, especially surgical room has a particular sensitivity [11] and is considered as the most vital unit in medical centers [12].…”

Simulation-Based Rolling Horizon Scheduling for Operating Theatres

“…Studies can mainly be categorized into considering completely deterministic "off-line" problems [4,6,12,30,33], to incorporating uncertainty features such as random procedure time [1,9,17] and disruptions caused by emergency demand [11,17]. Surprisingly, we only encountered two studies on the allocation of patients where stochastic future arrivals were accounted for [23,34]. However, Samudra et al [25] show that incorporating stochasticity constitutes more than half of the papers on OT planning.…”

“…Another study that accounts for uncertain future arrivals is Zhang et al [34]. Similar to the approach by Fei et al, they use a model that consists of two phases.…”