An optimization model for line planning and timetabling in automated urban metro subway networks. A case study

In this paper we present a Mixed Integer Linear Programming model that we developed as part of a pilot study requested by the R&D company Metrolab® in order to design tools for finding solutions for line planning and timetable situations in automated urban metro subway networks. Our model incorp...

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Detalles Bibliográficos
Autores: Blanco, Víctor, Conde Sánchez, Eduardo, Hinojosa Bergillos, Yolanda, Puerto Albandoz, Justo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/154613
Acceso en línea:https://hdl.handle.net/11441/154613
https://doi.org/10.1016/j.omega.2019.102165
Access Level:acceso abierto
Palabra clave:Line planning
Short-turns
Timetabling
Mixed integer linear programming
Matheuristic
Descripción
Sumario:In this paper we present a Mixed Integer Linear Programming model that we developed as part of a pilot study requested by the R&D company Metrolab® in order to design tools for finding solutions for line planning and timetable situations in automated urban metro subway networks. Our model incorporates important factors in public transportation systems from both, a cost-oriented and a passenger-oriented perspective, as time-dependent demands, interchange stations, short-turns and technical features of the trains in use. The incoming flows of passengers are modeled by means of piecewise linear demand functions which are parameterized in terms of arrival rates and bulk arrivals. Decisions about frequencies, train capacities, short-turning and timetables for a given planning horizon are jointly integrated to be optimized in our model. Finally, a novel matheuristic approach is proposed to solve the problem. The results of extensive computational experiments are reported to show its applicability and effectiveness to handle real-world subway networks.