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This study optimizes operating room scheduling to cut costs and improve efficiency. An artificial bee colony algorithm effectively minimizes costs and maximizes operating room utilization for large-scale surgical scheduling.

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Area of Science:

  • Healthcare Management
  • Operations Research
  • Computer Science

Background:

  • Operating room departments are a major source of hospital costs.
  • Efficient operating room scheduling is crucial for cost reduction and quality care.
  • Current scheduling strategies often struggle with complex optimization demands.

Purpose of the Study:

  • To develop and evaluate an effective algorithm for operating room scheduling.
  • To minimize total operating costs while maximizing operating room utilization.
  • To address the challenge of minimizing overtime use in surgical scheduling.

Main Methods:

  • A revised mathematical model was developed for optimal solutions up to 110 surgical cases.
  • Two heuristics, earliest due date (EDD) and longest processing time (LPT), were modified for feasible solutions.
  • An artificial bee colony (ABC) algorithm was proposed, incorporating advanced optimization techniques.

Main Results:

  • The ABC algorithm found optimal solutions for surgery sizes between 40 and 100 cases.
  • For problems larger than 110 cases, the ABC algorithm outperformed the EDD and LPT heuristics.
  • The proposed ABC algorithm demonstrated significant efficiency in solving large-scale operating room scheduling problems.

Conclusions:

  • The artificial bee colony algorithm is a promising approach for complex operating room scheduling.
  • This method effectively balances cost reduction, operating room utilization, and overtime minimization.
  • The findings suggest a practical tool for improving hospital operational efficiency.