Underground transportation is crucial in big modern cities as a way to achieve a clean, rapid and massif transport. While in peak hours the first objective is to move as many people as possible increasing the train frequency, in off-peak hours other considerations can be taken into account. Energy consumption should be an important issue in the design of train timetables in off-peak hours. Energy saving can be obtained by using regenerative brakes and allowing to synchronize the speed-up of a train exiting a station and the slow-down of a train arriving to another station connected to the same electric section. The arriving train generates electricity that is consumed by the departing train. In fact, given the high frequency of trains in peak hours it is more probable the coincidence of these two processes and, at the same time, is more difficult to change the train schedules by the same reason. Thus the first step in energy saving by changing the off-peak train timetable is maximizing the time overlap between different trains in the same or in different stations connected to the same electrical substation.

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Mathematical programming approach to underground timetabling problem for maximizing time synchronization

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Trends in Models and Algorithms for Fleet Management

A simulation study of the fleet sizing problem arising in offshore anchor handling operations

This paper considers the locomotive assignment problem encountered during the planning of the operations of a freight railroad, which consists of providing sufficient motive power to pull a set of scheduled trains at minimum cost while satisfying locomotive availability and maintenance requirements. In 1997, Ziarati et al. proposed for this problem a heuristic branch-and-price approach that relies on a simple depth-first search strategy without backtracking. In this paper, we present an efficient backtracking mechanism that can be added to this heuristic branch-and-price approach. To do so, we propose and evaluate different branching methods that impose multiple decisions on locomotive routes at each branching node, including one decision that forbids one such route. Finally, we introduce different ways of computing an estimate of the best integer solution value that can be obtained from a branch-and-bound node. These estimates can be used to guide the backtracking process of a two-phase search strategy.

An Extended Branch-and-Bound Method for Locomotive Assignment

This paper addresses the fleet renewal problem and particularly the treatment of uncertainty in the maritime case. A stochastic programming model for the maritime fleet renewal problem is presented. The main contribution is that of assessing whether or not better decisions can be achieved by using stochastic programming rather than employing a deterministic model and using average data. Elements increasing the relevance of uncertainty are also investigated. Tests performed on the case of Wallenius Wilhelmsen Logistics, a major liner shipping company, show that solutions to the model we present perform noticeably better than solutions obtained using average values.

Uncertainty in Fleet Renewal: A Case from Maritime Transportation

Determination of fleet size of locomotives and of a policy to deadhead them are tactical issues that influence the level of customer service in a rail network. This paper considers a railroad system in which a priori freight train schedule does not exist. A simulation-based approach is proposed for tactical locomotive fleet sizing. The study shows that the throughput increases with the number of locomotives upto a certain level; after that the congestion caused by the movements of large number of locomotives in the capacity-constrained rail network offsets the potential benefit of a large fleet.

Tactical Locomotive Fleet Sizing for Freight Train Operations

In many countries, freight trains have to share a rail network with passenger trains. In this paper, we consider a situation where passenger trains must adhere to a strict published schedule, whereas freight train movements can be inserted at any convenient time, without disrupting scheduled passenger trains. We propose an algorithm for the problem of routing and scheduling of a single freight train in a passenger rail network. However, the multiple freight train routing and scheduling problem is shown to be NP-complete, even for simplified instances. Specifically, we show that both routing and scheduling of freight trains are difficult, even when only two freight trains are considered. It is also difficult when freight train movements are restricted to reach their destinations with no idling permitted at intermediate stations. We have developed a Stepwise Dispatching Heuristic for routing and scheduling multiple freight trains in a passenger rail network. Computational results confirm the efficacy of our algorithm for single freight train routing and of the proposed Stepwise Dispatching Heuristic.

Freight train routing and scheduling in a passenger rail network: computational complexity and the stepwise dispatching heuristic

Locomotive assignment and freight train scheduling using genetic algorithms

This paper addresses the problem of routing and scheduling freight trains in a rail network where passenger trains must adhere to a strict schedule and freight train movements can be inserted at any time or as demands arise, without disrupting passenger trains. An exemplar of such a situation is the Indian Railway System. The problem is formulated as a 0–1 mixed integer programme to minimise the sum of travel times of the freight trains in a passenger rail network, for which a lower bound is developed. We propose a hierarchical permutation heuristic, which identifies the route and schedule for freight trains one at a time in a passenger rail network. A number of dispatching rules are proposed for identifying the best hierarchy in which trains must be scheduled. We report the computational experience for solving various problems based upon real data.

A heuristic for routing and scheduling freight trains in a passenger rail network

https://www.onlinelibrary.wiley.com/doi/pdf/10.1002/atr.1395

T. Godwin

Papers

Tactical Locomotive Fleet Sizing for Freight Train Operations

Freight train routing and scheduling in a passenger rail network: computational complexity and the stepwise dispatching heuristic

Locomotive assignment and freight train scheduling using genetic algorithms

A heuristic for routing and scheduling freight trains in a passenger rail network

Finding time-robust fuel-efficient paths for a call-taxi in a stochastic city road network