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Genetic Algorithm–Based Outpatient Appointment Scheduling Systems
Author(s) -
Song Foh Chew,
Clariecia Groves
Publication year - 2015
Publication title -
journal of healthcare technology and management
Language(s) - English
Resource type - Journals
eISSN - 2163-1328
pISSN - 2163-131X
DOI - 10.7726/jhtm.2015.1001
Subject(s) - computer science , genetic algorithm , scheduling (production processes) , algorithm , mathematical optimization , mathematics , machine learning
Outpatient appointment scheduling for a clinic is a problem of assigning appointment times to patients that seek non-emergency medical attention. This paper employs genetic algorithms to find optimal or near optimal numbers of advanced appointment and walk-in patients to assign to each time block for a day. To this end, an outpatient appointment schedule is represented by a vector in which a component indicates the number of patients to be assigned to the corresponding time block. The goal is to maximize profit for the clinic subject to such factors as the number of time blocks for a day, no-show rates, mean service times, unit revenues, patient wait time unit cost, staff idle time unit costs, and staff overtime unit costs. Our results reveal that all factors are influential in maximizing the profit except the staff overtime unit costs.

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