@article{10902/15865, year = {2018}, month = {7}, url = {http://hdl.handle.net/10902/15865}, 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.}, organization = {Acknowledgements. This work was supported by the Spanish Government [Grant Nos.TIN2016-79190-R, MTM2014-55262-P].}, publisher = {Elsevier}, publisher = {Computers & industrial engineering, Volume 121, July 2018, Pages 51-61}, title = {Genetic fuzzy schedules for charging electric vehicles}, author = {García Álvarez, Jorge and González Rodríguez, Inés and Vela, Camino R. and González, Miguel A. and Afsar, Sezin}, }