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Conference Papers Year : 2022

Optimizing a Dynamic Outpatient Facility System with Multiple Servers

Abstract

The management of queues is a complex problem, and it requires special attention in dynamic environments where information changes over time. This work focuses on an outpatient facility system where patients are attended by identical parallel servers offering different services. Each patient requires service and expects to receive it within a given target time, after which, a tardiness is created. The objective of the problem is to minimize the total tardiness while defining which services each server will offer during the working hours. The arrival of patients is dynamic, and the server’s configurations of services can be updated from time to time. To solve the problem, we propose a local search-based heuristic that locally assigns a configuration to each server based on the improvement reached in terms of total tardiness. The heuristic is tested on realistic instances, considering different settings, showing its superiority over the solution currently implemented on the facility system.
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Dates and versions

emse-04606329 , version 1 (10-06-2024)

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Beatrice Bolsi, Arthur Kramer, Thiago Alves de Queiroz, Manuel Iori. Optimizing a Dynamic Outpatient Facility System with Multiple Servers. Optimization in Artificial Intelligence and Data Sciences, Sep 2022, Rome, Italy. pp.247-258, ⟨10.1007/978-3-030-95380-5_22⟩. ⟨emse-04606329⟩

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