TY - JOUR
T1 - A column-generation-heuristic-based benders’ decomposition for solving adaptive allocation scheduling of patients in operating rooms
AU - Kamran, Mehdi A.
AU - Karimi, Behrooz
AU - Dellaert, Nico
PY - 2020/10
Y1 - 2020/10
N2 - This paper investigates the Adaptive Allocation Scheduling Problem with a modified block scheduling policy, in which candidate patients have to be assigned and sequenced into operating room blocks, taking into consideration unanticipated events or disruptions (e.g., arrivals of non-elective patients). A post disruption management approach is considered to tackle the disruptions. In this regard, a mixed-integer linear programming model with multiple objectives including minimization of patients’ cancellation, patients’ tardiness, block overtime, idleness of surgeons, and minimizing the start time of emergency patient's surgery is proposed. A solution approach consisting of a column-generation-based heuristic algorithm and a Benders’ decomposition technique is developed to solve the model. The efficiency of the formulation and the solution approach is examined through numerical experiments based on hospital records. It is shown that the developed solution approach outperforms the untutored column generation method and is capable of finding close to optimal solutions significantly faster than the standard Benders’ decomposition method.
AB - This paper investigates the Adaptive Allocation Scheduling Problem with a modified block scheduling policy, in which candidate patients have to be assigned and sequenced into operating room blocks, taking into consideration unanticipated events or disruptions (e.g., arrivals of non-elective patients). A post disruption management approach is considered to tackle the disruptions. In this regard, a mixed-integer linear programming model with multiple objectives including minimization of patients’ cancellation, patients’ tardiness, block overtime, idleness of surgeons, and minimizing the start time of emergency patient's surgery is proposed. A solution approach consisting of a column-generation-based heuristic algorithm and a Benders’ decomposition technique is developed to solve the model. The efficiency of the formulation and the solution approach is examined through numerical experiments based on hospital records. It is shown that the developed solution approach outperforms the untutored column generation method and is capable of finding close to optimal solutions significantly faster than the standard Benders’ decomposition method.
KW - Adaptive allocation scheduling problem
KW - Benders’ decomposition
KW - Column-generation-based heuristic
KW - Disruption management
KW - Elective and non-elective patients
UR - http://www.scopus.com/inward/record.url?scp=85089240953&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2020.106698
DO - 10.1016/j.cie.2020.106698
M3 - Article
AN - SCOPUS:85089240953
SN - 0360-8352
VL - 148
JO - Computers & Industrial Engineering
JF - Computers & Industrial Engineering
M1 - 106698
ER -