This talk introduces the concept of metaheuristics, algorithms used to solve difficult optimization problems, by illustrating in parallel their implementation and use using julia, a high-level and high-performance programming language. Some approaches we will cover include the greedy heuristic, the greedy randomized search procedure, descent methods, variable neighborhood search, simulated annealing, tabu search and genetic algorithms.
Target audience : Master students, Bachelor students with interest in optimization, PhD training, anyone with some knowledge of programming but not particularly familiar with metaheuristics.
Recommended packages (open source): Julia 1.7.2, Anaconda3 / Jupyter
Fecha: martes 24 de mayo de 2022
Lugar: Sala de Audiovisuales, Escuela de Enxeñería Industrial, sede Campus
Hora: 16:00 h
Se emitirá simultáneamente a través de la sala REU de la EEI-Campus: https://campusremotouvigo.gal/access/public/meeting/312934181
Clave de alumno: cYW2XD5F
Campus Remoto directions
Más información en eei.exteriores@uvigo.es
