Robust receding horizon control strategy for replenishment planning of pharmacy robotic dispensing systems - Dauod, Husam; Serhan, Duaa; Wang, Haifeng; Khader, Nourma; Won Yoon, Sang; Srihari, Krishnaswami (Robotics and computer-integrated manufacturing, 2019)
•Studied the replenishment problem of robotic dispensing systems in central fill pharmacies.•Developed a robust mixed integer programming model to make replenishment decisions.•Proposed a robust receding horizon control strategy that considers stochastic variables.•Compared the proposed strategy against other optimization strategies.•Analyzed the results of different scenarios. [Display omitted] This paper presents a robust receding horizon control strategy (RHC-RO) to enhance replenishment planning and inventory control of robotic dispensing systems in central fill pharmacies (CFPs). Replenishment in CFPs is a key process greatly influenced by several stochastic factors, such as demand volume and process times. In this research, a robust mixed integer quadratic programming (RMIQP) model is proposed to determine the number of allocated canisters and the schedule of replenishment operations considering multiple scenarios. A receding horizon control (RHC) mechanism, which divides the optimization horizon into smaller time windows, is applied to enhance the solution quality and reduce the computational burden. The proposed RHC-RO strategy is evaluated using simulation against offline, robust optimization (RO), and RHC strategies in terms of total replenishment costs. The results indicate that RHC-RO outperforms the offline, RO, and RHC strategies by generating 19.7%, 18.3%, and 5.6% less replenishment costs on average, respectively. The results also show that the RHC-RO strategy enables timely, accurate, and robust replenishment decisions.