Real-time Dispenser Replenishment Optimization Based on Receding Horizon Control

Husam Dauod; Haifeng Wang; Nourma Khader; Sang Won Yoon; Krishnaswami Srihari

doi:10.1016/j.promfg.2017.07.313

Real-time Dispenser Replenishment Optimization Based on Receding Horizon Control

Husam Dauod
, Haifeng Wang
, Nourma Khader
, Sang Won Yoon
, Krishnaswami Srihari

School of Sys Sci Ind Engr

Binghamton University

State University of New York Binghamton University

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

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%.

Original language	English
Pages (from-to)	1782-1789
Number of pages	8
Journal	Procedia Manufacturing
Volume	11
DOIs	https://doi.org/10.1016/j.promfg.2017.07.313
State	Published - 2017

Keywords

Optimization
inventory planning and control
mixed integer programming
receding horizon control

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10.1016/j.promfg.2017.07.313

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title = "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\%.",

keywords = "Optimization, inventory planning and control, mixed integer programming, receding horizon control",

author = "Husam Dauod and Haifeng Wang and Nourma Khader and Yoon, \{Sang Won\} and Krishnaswami Srihari",

note = "Publisher Copyright: {\textcopyright} 2017 The Authors",

year = "2017",

doi = "10.1016/j.promfg.2017.07.313",

language = "English",

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pages = "1782--1789",

journal = "Procedia Manufacturing",

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T1 - Real-time Dispenser Replenishment Optimization Based on Receding Horizon Control

AU - Dauod, Husam

AU - Wang, Haifeng

AU - Khader, Nourma

AU - Yoon, Sang Won

AU - Srihari, Krishnaswami

PY - 2017

Y1 - 2017

N2 - 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%.

AB - 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%.

KW - Optimization

KW - inventory planning and control

KW - mixed integer programming

KW - receding horizon control

UR - https://www.scopus.com/pages/publications/85029876584

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DO - 10.1016/j.promfg.2017.07.313

M3 - Article

SN - 2351-9789

VL - 11

SP - 1782

EP - 1789

JO - Procedia Manufacturing

JF - Procedia Manufacturing

ER -

Real-time Dispenser Replenishment Optimization Based on Receding Horizon Control

Abstract

Keywords

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