Modeling and control of drug assignment for pharmaceutical cabinets using discrete event systems approaches

Abstract

The public health sector, considered to be vital, especially in this pandemic crisis of COVID‐19, requires automation and control of drug distribution in pharmacies commonly called: “Dispensing.” In this paper, we address the medication assignment problem for automated dispensing cabinets (ADCs). First, we use a network of conflicting timed event graphs (CTEGs), a class of timed Petri nets with shared resources, to model pharmaceutical cabinets. Second, we develop a new method for controlling CTEGs under mutual exclusion constraints (MECs) to solve the problem of drug assignment, using a control approach based on Min‐Plus algebra. Finally, a case study of assigning drugs is given to illustrate the proposed methodology and show the efficiency of the developed control laws.