Real-time Dispenser Replenishment Optimization Based on Receding Horizon Control

Abstract This paper presents a real-time optimization approach to enhance dispenser replenishment planning in central fill pharmacy systems. Dispenser replenishment is a key function that directly impacts the overall pharmacy performance. It is influenced by various stochastic variables such as demand variety, counting speed, and medication size. These variables increase the complexity of planning, especially when demand volume is high. In this research, a mixed integer programming model is proposed to minimize the total replenishment costs. A receding horizon control (RHC) mechanism is applied to reduce the computational burden and enhance the solution's quality. Experimental results indicate that dynamic planning using RHC reduces the total replenishment costs by 64%.