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%.