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Related Experiment Video

Updated: Oct 2, 2025

Emergency Undocking in Robotic Surgery: A Simulation Curriculum

Emergency Undocking in Robotic Surgery: A Simulation Curriculum

Published on: May 20, 2018

Operating Room Planning for Emergency Surgery: Optimization in Multiobjective Modeling and Management from the Latest

Qiqian Li¹, Yali Liu², Esra Sipahi Döngül³

¹The Seventh Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China.

Computational Intelligence and Neuroscience

|February 28, 2022

Summary

This summary is machine-generated.

This study optimizes operating room scheduling for emergency surgeries, balancing costs and maximizing procedures. A robust optimization approach handles uncertain surgery times, improving scheduling efficiency.

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Area of Science:

Operations Research
Healthcare Management
Applied Mathematics

Background:

Efficient operating room scheduling is crucial for healthcare systems.
Uncertainty in surgery duration poses a significant challenge to OR planning.
Balancing emergency and elective surgery needs requires sophisticated optimization.

Purpose of the Study:

To develop an optimization model for operating room scheduling considering surgery priorities.
To minimize costs of elective and emergency surgeries while maximizing scheduled procedures.
To incorporate surgeon assistants and address uncertain surgery times using robust optimization.

Main Methods:

A robust optimization approach was applied to handle uncertain surgery durations.
The model considered surgeon assistants for surgical procedures.
GAMS software was used for analysis, alongside a hybrid simulation and Gray Wolf Optimization (GWO) algorithm.

Main Results:

Increased risk parameters in the robust optimization model led to higher system costs.
The hybrid GWO simulation method yielded solutions 73.75% better on average than the standalone GWO algorithm under uncertainty.
The proposed optimization approach demonstrated effectiveness in a real-world hospital case study.

Conclusions:

Robust optimization effectively manages uncertainty in operating room scheduling.
Hybrid simulation with GWO offers superior solutions for complex OR scheduling problems.
The developed model provides a valuable tool for improving hospital operational efficiency and surgical throughput.