Ant Colony System for Effective Doctor Rostering

Designing effective schedules for medical staff is vital in the healthcare industry as it directly impacts the efficiency of medical institutions, patient care, and staff satisfaction.To tackle this challenge, we suggest utilizing a binary programming model in combination with the ant colony system (ACS) approach.We have tailored the ACS method to address the constraints and requirements of medical staff scheduling, including adaptations to the pheromone matrix and the heuristic information.Numerical results illustrate our method's efficiency in generating optimal schedules, and we analyze how variations in ACS parameters affect the search process.These experiments highlight the robustness of our approach and pave the way for a promising future of further theoretical analysis and algorithm refinement.