Solving the planning and scheduling problem simultaneously in a hospital with a bi-layer discrete particle swarm...

Area of Science:

• Operations Research
• Healthcare Management
• Computer Science

Background:

• Operating rooms are critical, capital-intensive hospital resources.
• Improving efficiency and controlling costs are key hospital objectives.
• Current operating room scheduling faces challenges in balancing patient satisfaction and operational costs.

Purpose of the Study:

• To address the NP-hard problem of joint operating room planning and scheduling on a weekly basis.
• To maximize patient satisfaction while minimizing overtime and daily operational costs.
• To develop an effective optimization method for complex healthcare resource management.

Main Methods:

• A bi-layer discrete particle swarm optimization algorithm was developed.
• The method incorporates a repair mechanism for infeasible solutions and specific operators (crossover, insertion, exchange).
• A gap finding scheduling heuristic was designed for surgical case sequencing.

Main Results:

• The proposed optimization method was compared against existing approaches using data from a Chinese hospital.
• Efficient Pareto solutions for the joint operating room planning and scheduling problem were identified.
• The bi-layer discrete particle swarm optimization demonstrated efficient and effective performance.

Conclusions:

• The developed bi-layer discrete particle swarm optimization is a viable solution for operating room scheduling.
• This approach can significantly enhance hospital operational efficiency and resource utilization.
• The findings contribute to optimizing healthcare resource management and reducing operational costs.