Conference Papers 2022

Seminar
Day 1 (7 Sep 2022), Session 1, MODE SHIFT POTENTIAL, 11:00 - 13:00

Status
Accepted, documents submitted

Submitted by / Abstract owner
Maurice Krauth

Authors
Maurice Krauth,
Daniel Haalboom,
Philipp Salger

Short abstract
This paper analyses potentials for single wagonload network control in objective decision-making when a disruption occurs. A simulation model is developed. Parameters changed by a disruption are processed in an optimisation model and then fed back.

Abstract
Considering climate policy goals and an intended shift of freight traffic, rail offers an opportunity to encounter the increasing GHG emissions. Single wagonload transport is a type of rail freight transport in which railcars from different senders to receivers are routed through a single hub and spoke based network. At intermediate nodes, the railcars are consolidated with other railcars until they reach their destination. Time-critical shipments in particular are currently transported mainly by truck or air freight due to the higher reliability regarding the agreed delivery appointments. To improve the reliability of the rail network and intervene in the event of disruption, control mechanisms are necessary.

The aim of this paper is to analyse network control in dealing with disruptions that occur during operation of the network. Objective decision making in dealing with disruptions enables an optimal schedule adjustment and thus a minimization of disruption consequences. Introducing an exemplary single wagonload network, several scenarios are designed to represent different network states. A simulation of the network which takes stochastic disruption events into account enables the determination of parameters such as an adapted train framework.

The determined parameters are processed and serve as input for a novel optimisation model. This model optimises the routing plan taking into account the parameters determined by simulation. The parameters determined from this can now be fed back into the simulation and thus iteratively adjust to changing conditions. Ultimately, this process can provide an improved response to stochastic events.

In order to fulfil the aim of this paper we conduct computational experiments for the different scenarios. The experiments enable an analysis of the effects within the different scenarios and thus a better understanding of complex decision making in case of disruption occurrence. In addition, the experiments allow to determine expected transport times.

This work contributes to the controller's ability to make objective decisions when resolving disruptions in single wagonload transport.

Programme committee
Rail Policy and Planning