Robust receding horizon control strategy for replenishment planning of pharmacy robotic dispensing systems

•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 aga...

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Veröffentlicht in:Robotics and computer-integrated manufacturing Jg. 59; S. 177 - 188
Hauptverfasser: Dauod, Husam, Serhan, Duaa, Wang, Haifeng, Khader, Nourma, Won Yoon, Sang, Srihari, Krishnaswami
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.10.2019
Elsevier BV
Schlagworte:
Cans
Computer simulation
Dispensing
Horizon
Inventory control
Inventory management and control
Mixed integer
Optimization
Quadratic programming
Receding horizon control
Replenishment
Robot control
Robust control
Robust optimization
Schedules
Strategy
Windows (intervals)
Receding horizon control
Inventory management and control
Robust optimization
ISSN:0736-5845, 1879-2537
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Zusammenfassung:•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.
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ISSN:0736-5845
1879-2537
DOI:10.1016/j.rcim.2019.04.001