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proposed an evolutionary algorithm to deal with the issue of multiple resources constraints in their study. Fig.
1. show the surgical procedure phase (Belkhamsa, Jarboui, & Masmoudi, 2018). We illustrate the part the
surgical scheduling problem may happen that relate to an issue that already states previously.

2. Issue Representation

From the analysis of previous studies, we categories the issue in surgical scheduling problem into three types
which are: (1) Uncertainty; (2) Capacity Planning; and (3) Request and Demand. In this section, we discuss the

The area
may happen The area may
uncertainty happen
or request capacity
and demand planning
issue issue

Fig. 1. Surgical procedure phase

uncertainty issue that commonly arises in surgical scheduling. We then address the capacity issue that relates to
resources planning, and subsequently, the problems of request and demand related to the surgical case criteria
and surgical team preference.

2.1 Uncertainty

Uncertainty is the most crucial issue that arises in surgical scheduling. Surgery duration is one of the reasons
that cause the uncertainty issue (J. M. van Oostrum, Van Houdenhoven, Hurink, Hans, Wullink, & Kazemier,
2008). The surgery’s duration is unknown due to the procedure’s unforeseen start time and leads to an increase
in overtime (Zhang, Wang, Tang, & Lim, 2020). Overtime is a frequent occurrence in surgery units, resulting
in increasing surgery team or patient stress or dissatisfaction and financial loss for hospitals (Zhang, Wang,
Tang, & Lim, 2020). (Silva & de Souza, 2020) discussed the uncertainty on when emergency and urgent surgery
will arrive. When emergency and urgent surgery occurs without warning or intervention, the confusion about
its arrival will be exposed.
Furthermore, the uncertainty issue also may happen due to the recovery time for the patient. For example,
(Zhu, Zhang, Jiao, & Li, 2015) state uncertainty may arise due to the patient's recovery time by the anaesthesia
after the surgery. (Wiyartanti, Park, Chung, Kim, Sohn, & Kwon, 2015) stated that when many surgical cases
need immediate changes in data, such as when surgery delays or cancellation occurs on the same day, confusion
can arise from the patient or the surgical procedure itself.
2.2 Capacity Planning

(Chow, Puterman, Salehirad, Huang, Atkins, & Management, 2011) study the way to improve the surgical
scheduling caused by the high surgical bed utilisation. Because of the capacity problem, this situation is

E- Proceedings of The 5th International Multi-Conference on Artificial Intelligence Technology (MCAIT 2021) [144]
Artificial Intelligence in the 4th Industrial Revolution