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Genetic fuzzy schedules for charging electric vehicles

Abstract: This work tackles the problem of scheduling the charging of electric vehicles in a real-world charging station subject to a set of physical constraints, with the goal of minimising the total tardiness with respect to a desired departure date given for each vehicle. We model a variant of the problem that incorporates uncertainty in the charging times using fuzzy numbers. As solving method, we propose a genetic algorithm with tailor-made operators,in particular, a new chromosome evaluation method based on generating schedules from a priority vector. Finally, an experimental study avails the proposed genetic algorithm both in terms of algorithm convergence and quality of the obtained solutions.

 Autoría: García-Álvarez J., González-Rodríguez I., Vela C.R., González M.A., Afsar S.,

 Fuente: Computers & industrial engineering, 2018, 121, 51-61

 Editorial: Elsevier

 Fecha de publicación: 01/07/2018

 Nº de páginas: 11

 Tipo de publicación: Artículo de Revista

 DOI: 10.1016/j.cie.2018.05.019

 ISSN: 0360-8352,1879-0550

 Proyecto español: TIN2016-79190-R ; MTM2014-55262-P

 Url de la publicación: https://doi.org/10.1016/j.cie.2018.05.019

Autoría

GARCÍA ÁLVAREZ, JORGE

CAMINO RODRIGUEZ VELA

GONZÁLEZ, MIGUEL A.

AFSAR, SEZIN