SELECTED ASPECTS OF THE TRAIN TIMETABLE CONSTRUCTION OF PASSENGER TRAINS WITH THE CONSIDERATION OF PLATFORM EDGES AND STABLING TRACKS ALLOCATION PROBLEM

The aim of the article is to present a method concerning the problem of the construction of timetable from the point of view of the assignment of platform edges and stabling tracks. Taking into account these two issues in the method is extremely important from the point of view of the fluency of railway traffic, as well as minimizing railway undertaking costs related to access to the infrastructure offered by the manager in terms of occupying the platform edge above the set time. The paper describes the issues of allocating platform edges and stabling tracks in operating offices, with particular consideration of the costs related to this. The formulation of the problem of the train timetable construction was presented, including the allocation of edges and stabling tracks in a mathematical manner. In the model specified those parts that are relevant to the research problem considered in the article. In addition, the algorithm of the construction method with the use of a block diagram was discussed

A review of timetabling and resource allocation models for light-rail transportation systems

This paper surveys the relevant operations research literature on timetabling and resource allocationproblems with a special attention paid to the transportation systems. The purpose of this review is to define the critical objectives, determine the key components and identify the key issues for developing a comprehensive mathematical model for timetabling of light rail transit vehicles in sequence with the assignment of drivers as an available resource. In doing so, the implications of the emerging timetabling research is discussed, components of the mathematical models proposed are reviewed, and the extend they reflect real business practices are analyzed. Finally, fundamental issues and primary elements of a simple model in association with general timetabling and resource allocation problems are presented

Railway Crew Rescheduling with Retiming

Railway operations are disrupted frequently, e.g. the Dutch railway network experiences about three large disruptions per day on average. In such a disrupted situation railway operators need to quickly adjust their resource schedules. Nowadays, the timetable, the rolling stock and the crew schedule are recovered in a sequential way. In this paper, we model and solve the crew rescheduling problem with retiming. This problem extends the crew rescheduling problem by the possibility to delay the departure of some trains. In this way we partly integrate timetable adjustment and crew rescheduling. The algorithm is based on column generation techniques combined with Lagrangian heuristics. In order to prevent a large increase in computational time, retiming is allowed only for a limited number of trains where it seems very promising. Computational experiments with real-life disruption data show that, compared to the classical approach, it is possible to find better solutions by using crew rescheduling with retiming.

Smooth and controlled recovery planning of disruptions in rapid transit networks

This paper studies the disruption management problem of rapid transit rail networks. We consider an integrated model for the recovery of the timetable and the rolling stock schedules. We propose a new approach to deal with large-scale disruptions: we limit the number of simultaneous schedule changes as much as possible, and we control the length of the recovery period, in addition to the traditional objective criteria such as service quality and operational costs. Our new criteria express two goals: the recovery schedules can easily be implemented in practice, and the operations quickly return to the originally planned schedules after the recovery period. We report our computational tests on realistic problem instances of the Spanish rail operator RENFE and demonstrate the potential of this approach by solving different variants of the proposed model

Real-time train driver rescheduling by actor-agent techniques

Passenger railway operations are based on an extensive planning process for generating the timetable, the rolling stock circulation, and the crew duties for train drivers and conductors. In particular, crew scheduling is a complex process. After the planning process has been completed, the plans are carried out in the real-time operations. Preferably, the plans are carried out as scheduled. However, in case of delays of trains or large disruptions of the railway system, the timetable, the rolling stock circulation and the crew duties may not be feasible anymore and must be rescheduled. This paper presents a method based on multi-agent techniques to solve the train driver rescheduling problem in case of a large disruption. It assumes that the timetable and the rolling stock have been rescheduled already based on an incident scenario. In the crew rescheduling model, each train driver is represented by a driver-agent. A driver-agent whose duty has become infeasible by the disruption starts a recursive task exchange process with the other driver-agents in order to solve this infeasibility. The task exchange process is supported by a route-analyzer-agent, which determines whether a proposed task exchange is feasible, conditionally feasible, or not feasible. The task exchange process is guided by several cost parameters, and the aim is to find a feasible set of duties at minimal total cost. The train driver rescheduling method was tested on several realistic disruption instances of Netherlands Railways (NS), the main operator of passenger trains in the Netherlands. In general the rescheduling method finds an appropriate set of rescheduled duties in a short amount of time. This research was carried out in close cooperation by NS and the D-CIS Lab

A lexicographic optimization approach for berth schedule recovery problem in container terminals

In container terminals, the planned berth schedules often have to be revised because of disruptions caused by severe weather, equipment failures, technical problems and other unforeseen events. In this paper, the problem of berth schedule recovery is addressed to reduce the influences caused by disruptions. A multi-objective, multi-stage model is developed considering the characteristics of different customers and the trade-off of all parties involved. An approach based on the lexicographic optimization is designed to solve the model. Numerical experiments are provided to illustrate the validity of the proposed Model A and algorithms. Results indicate that the designed Model A and algorithm can tackle the berth plan recovery problem efficiently because the beneficial trade-off among all parties involved are considered. In addition, it is more flexible and feasible with the aspect of practical applications considering that the objective order can be adjusted by decision makers

Disruption management in passenger railway transportation.

This paper deals with disruption management in passengerrailway transportation. In the disruption management process, manyactors belonging to different organizations play a role. In this paperwe therefore describe the process itself and the roles of thedifferent actors.Furthermore, we discuss the three main subproblems in railwaydisruption management: timetable adjustment, and rolling stock andcrew re-scheduling. Next to a general description of these problems,we give an overview of the existing literature and we present somedetails of the specific situations at DSB S-tog and NS. These arethe railway operators in the suburban area of Copenhagen, Denmark,and on the main railway lines in the Netherlands, respectively.Since not much research has been carried out yet on OperationsResearch models for disruption management in the railway context,models and techniques that have been developed for related problemsin the airline world are discussed as well.Finally, we address the integration of the re-scheduling processesof the timetable, and the resources rolling stock and crew.

Column generation with dynamic duty selection for railway crew rescheduling

The Dutch railway network experiences about three large disruptions per day on average. In this paper, we present an algorithm to reschedule the crews when such a disruption occurs. The algorithm is based on column generation techniques combined with Lagrangian heuristics. Since the number of duties is very large in practical instances, we first define a core problem of tractable size. If some tasks remain uncovered in the solution of the core problem, we perform a neighborhood exploration to improve the solution. Computational experiments with real-life instances show that our method is capable of producing good solutions within a couple of minutes of Computation time

Railway Crew Rescheduling with Retiming

Railway operations are disrupted frequently, e.g. the Dutch railway network experiences about three large disruptions per day on average. In such a disrupted situation railway operators need to quickly adjust their resource schedules. Nowadays, the timetable, the rolling stock and the crew schedule are recovered in a sequential way. In this paper, we model and solve the crew rescheduling problem with retiming. This problem extends the crew rescheduling problem by the possibility to delay the departure of some trains. In this way we partly integrate timetable adjustment and crew rescheduling. The algorithm is based on column generation techniques combined with Lagrangian heuristics. In order to prevent a large increase in computational time, retiming is allowed only for a limited number of trains where it seems very promising. Computational experiments with real-life disruption data show that, compared to the classical approach, it is possible to find better solutions by using crew rescheduling with retiming