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2021 | OriginalPaper | Chapter

An ACO Algorithm for a Scheduling Problem in Health Simulation Center

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Abstract

SimUSanté is one of the biggest European simulating and training centers, proposing training sessions for all involed in healthcare: professionals, students, patients. This paper presents the timetabling problem encountered by SimUSanté with regard to the quality objectives and the time and resource constraints. To solve it, SimUACO-LS which is the hybridization of the Min-Max Ants Colony Optimization algorithm SimUACO with the variable neighborhood search SimULS [3], is presented. SimULS, SimUACO and SimUACO-LS are compared in a set of representative instances [2], newly generated and derived from those of the Curriculum-Based Course Timetabling problem [1]. SimUACO-LS always improves both results of SimULS and SimUACO by respectively 3.84% and 2.97%.

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Metadata
Title
An ACO Algorithm for a Scheduling Problem in Health Simulation Center
Authors
Simon Caillard
Corinne Lucet
Laure Brisoux-Devendeville
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-85902-2_36

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