G-DMP: An algorithm without constraint relaxation to solve the train departure matching problem

Alondra Rojas, Elizabeth Montero, Maria Cristina Riff

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferencia

Resumen

In this work we present a GRASP based approach for solving the departure matching problem, an important subproblem of the Rolling Stock Units Management problem. Our approach implements a constructive and a Local Search steps that are able to deal with all the constraints and costs related to the problem. We evaluate our approach using two sets of instances: a set of randomly generated instances and the set of instances used in ROADEF/EURO Challenge 2014.

Idioma originalInglés
Título de la publicación alojada2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas2382-2389
Número de páginas8
ISBN (versión digital)9781509046010
DOI
EstadoPublicada - 5 jul 2017
Evento2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Espana
Duración: 5 jun 20178 jun 2017

Conferencia

Conferencia2017 IEEE Congress on Evolutionary Computation, CEC 2017
PaísEspana
CiudadDonostia-San Sebastian
Período5/06/178/06/17

Áreas temáticas de ASJC Scopus

  • Inteligencia artificial
  • Redes de ordenadores y comunicaciones
  • Informática aplicada
  • Procesamiento de senales

Huella Profundice en los temas de investigación de 'G-DMP: An algorithm without constraint relaxation to solve the train departure matching problem'. En conjunto forman una huella única.

  • Citar esto

    Rojas, A., Montero, E., & Riff, M. C. (2017). G-DMP: An algorithm without constraint relaxation to solve the train departure matching problem. En 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings (pp. 2382-2389). [7969593] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2017.7969593