Microscopic disruption management: energy consumption and passenger compensation optimisation

Rail operations are often disrupted by accidents that cause traffic to diverge from the scheduled operations, rendering it difficult to run the schedule as planned. In such a case, the operator must change the schedule to return to the original schedule. If passengers are delayed, a train operator m...

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Detalhes bibliográficos
Autores: Cadarso Morga, Luis, Codina Sancho, Esteve|||0000-0002-9431-6158, Garcia Ródenas, Ricardo
Formato: artículo
Fecha de publicación:2022
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/371321
Acesso em linha:https://hdl.handle.net/2117/371321
https://dx.doi.org/10.1016/j.trpro.2022.02.006
Access Level:acceso abierto
Palavra-chave:Operations research
Management science
Train re-schedulingPassenger compensationDelaysOptimal control
Investigació operativa
Administració--Models matemàtics
Classificació AMS::90 Operations research, mathematical programming
Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
Descrição
Resumo:Rail operations are often disrupted by accidents that cause traffic to diverge from the scheduled operations, rendering it difficult to run the schedule as planned. In such a case, the operator must change the schedule to return to the original schedule. If passengers are delayed, a train operator may have a policy of economically compensating them (e.g., refunding ticket fare). Compensation amounts are usually determined by the length of the delay. As a result, it is critical to have a smart way of determining whether to accelerate trains to absorb delays, thus increasing energy usage, or to compensate passengers. This paper presents a mathematical model for determining the speed profile while taking passenger usage into account. The model determines the best sequence of operating regimes and switching points between them for a variety of different situations and train types, all while accounting for delays and passenger compensation policies. The aim is to reduce both the amount of energy consumed and the amount of compensation paid to passengers. There are constraints on traction and braking forces, train velocity, forces induced by vertical and horizontal track profile, and passenger compensation policy. The results of computational tests performed on practical problem instances of the Spanish rail operator RENFE are showed. The suggested approach is capable of producing strategies that strike an excellent balance between different managerial objectives.