An ACO Algorithm for a Scheduling Problem in Health Simulation Center - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. IFIP WG 5.7 International Conference. Part II Access content directly
Conference Papers Year : 2021

An ACO Algorithm for a Scheduling Problem in Health Simulation Center

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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hal-03419847 , version 1 (09-06-2023)

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Simon Caillard, Corinne Lucet, Laure Brisoux Devendeville. An ACO Algorithm for a Scheduling Problem in Health Simulation Center. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.333-341, ⟨10.1007/978-3-030-85902-2_36⟩. ⟨hal-03419847⟩
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