are seeking to reduce their costs and improve their financial circumstances;
and on the other hand, they want to improve the level of patient satisfaction.
Moreover, operating rooms are one of the most important and costly departments
and a great source of income in hospitals. Hence, they have a significant impact on the hospital performance 2.
Due to abundant research related to
operating room scheduling, there is a wide-spreading literature on this
subject. The first review paper was presented in 1978 1.
However, because of growing number of elderly people and consequently
increasing demand for surgeries 3, the importance of operating room
scheduling has also significantly increased. Due to the conflicts in priorities and
preferences of stakeholders
as well as limitation of available resources, planning various
and at the same time important tasks at the department of operating rooms is a
difficult and complex job. All these
together, clearly indicate the importance of having an optimized schedule for operating

Generally, operating room scheduling problems can be categorized
based on the following criteria 22. Patient characteristics: Two types
of patients are considered in the literature on operating room scheduling,
elective and non-elective patients. Elective patients are the ones whom their
surgeries can be well planned in advance; non-elective patients are whom their
surgeries are unexpected and hence, need to be performed urgently. Adan and Vissers 4 consider both inpatients and outpatients in their research. In
their study, outpatients are treated as inpatients with duration of stay of one
day whom they do not necessarily need specialized resources. Wullink et al.
5, examined whether it is necessary to reserve a separate operating room or
to reserve some capacity in all elective operating rooms in order to improve
the responsiveness to emergencies. Performance measures: discussion of
the performance criteria includes some criteria such as patient and surgeon waiting time, utilization, makespan, financial
value, preferences or throughput, patient deferral, etc 6. Patient waiting may be interpreted as the stay on a surgery waiting
list or waiting time between 2 surgeries or waiting time because of lack of
operating room capacity, which decreases patient satisfaction. Surgeon waiting
time is interpreted to waiting time because of lack of readiness of patient or operating room
or inaccessibility of the operating room due to lack of capacity. Operating room overtime means that total time
of surgeries in an operating room is greater than scheduled time for
that operating room that causes extra cost for hospital. Denton et al. 7, examine how case sequencing affects
patient and surgeon waiting time and operating room overtime. Van Berkel and
Blake 8 used a discrete-event simulation to examine how a change in
throughput triggers a decrease in waiting time. In particular, they affect the throughput
by changing the capacity of beds in the wards and by changing the amount of available
operating room time. Decision level: it should be determined for
which managerial level a decision is being made. For instance, the decision is
related to operating room capacity, patients or surgeons. Uncertainty:
Some researchers considered uncertainty related to expected surgery duration,
patient’s arrival, or accessing to resources. Persson and Persson 9, describe
a discrete-event simulation model to study how resource allocation policies at
the department of orthopedics affect waiting time and utilization of emergency
resources, taking into account both patient arrival uncertainty and surgery
duration variability. Research Methodology: A
variety of techniques or methods are performed to evaluate and solve the operating
room scheduling issues. All operational research based techniques can be
summarized in two categories of discrete simulation and mathematical
programming optimization. Basson and Butler
10, Denton et al. 11, Dexter and Ledolter 12,
Ballard and Kuhl 13, Bowers and Mould 14, used the discrete-event
simulation to model and solve the operating room planning problems. Mulholland
et al. 15, P. Lebowitz 16, Dexter et al. 17,
and P´erez et al. 18
used a mathematical programming optimization technique to model these

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Generally, surgeries
in hospitals can be categorized as elective or non-elective surgery. Bouguerra et
al. 19, proposed a mathematical programming model to solve their problem.
They optimized two main objectives. The first objective is to maximize the
utilization of the operating rooms and the second objective is to minimize the
idle time between the elective surgeries. Zhao
and Li 20,
studied a model to schedule elective surgeries in operating rooms.
They proposed a mixed integer nonlinear programming (MINLP) model as well as a
constraint programming (CP) model to solve their problem. They considered three
aspects of the daily scheduling decisions, first, the number of operating rooms
to open, second, the allocation of surgeries to operating rooms, third, the
sequence of surgeries in each operating room. Nazeriani
et al. 21 studied an elective surgery case and proposed
an ant colony optimization (ACO) to solve their
problem. They considered 3 steps for an elective
surgery: 1- pre-surgery, 2- during surgery, 3- after surgery. Ranjbar and
Ghafourian 22 divided each surgery into 4 steps: 1- From the moment of putting patients on beds of operating rooms until
patients anesthesia, 2- surgery, 3- end of surgery and starting nurses’
tasks, 4- operating room cleaning.
In order to simplify, duration of steps 1, 3 and 4 was considered fixed for all patients. The objective
function of their study includes two parts: 1- minimize
surgeons overtime, 2- minimize surgeons’ waiting time between surgeries (operating room idling time). Rostami
23, considered a nonlinear programming model for scheduling and
optimal allocation of operating rooms. The objective function of his model is
to minimize the maximum delay and utilization time of operating rooms. By this objective function, surgeries and surgical
staffs are assigned to operating rooms in such a way that the duration between
two surgeries in an operating room as well as patient and surgeon waiting times
are decreased. Chenani et al. 24, proposed a meta-heuristic method to optimize the
allocation of hospital beds. In their study,
patients are generally divided into two groups of elective and non-elective

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