Leo G. Kroon

Returnable containers: an example of reverse logistics

textabstractConsiders the application of returnable containers as an example of reverse logistics. A returnable container is a type of secondary packaging that can be used several times in the same form, in contrast with traditional cardboard boxes. For this equipment to be used, a system for the return logistics of the containers should be available: this system should guarantee that the containers are transported from the recipients to the next senders, and that they are cleaned and maintained, if necessary. Outlines several ways in which the return of these containers can be organized. Also includes a case study involving the design of such a return logistic system in The Netherlands. Also describes a quantitative model that can be used to support the related planning process.

Passenger Railway Optimization

Publisher Summary Railway transportation can be split into passenger transportation and cargo transportation. This chapter discusses the European situation, where the major part of railway transportation consists of passenger transportation without addressing important problems in cargo transportation—such as car blocking, train makeup, train routing, and empty car distribution. The chapter describes several mathematical models and optimization techniques that have been developed for effectively supporting traditional planning processes in passenger railway transportation. A lot of research has been carried out in this area, both of a practical and theoretical nature. The results of this research are starting to be applied in practice. Real-time control is at the other side of the planning spectrum. The current trend in the railway industry is a shift from “planning in detail” to “effective real-time control.” Disturbances and disruptions in the railway operations are inevitable. Therefore, large parts of the operational plans are never carried out.

Decomposition of a Combined Inventory and Time Constrained Ship Routing Problem

In contrast to vehicle routing problems, little work has been done in ship routing and scheduling, although large benefits may be expected from improving this scheduling process. We will present a real ship planning problem, which is a combined inventory management problem anda routing problem with time windows. A fleet of ships transports a single product (ammonia) between production and consumption harbors. The quantities loaded and discharged are determined by the production rates of the harbors, possible stock levels, and the actual ship visiting the harbor. We describe the real problem and the underlying mathematical model. To decompose this model, we discuss some model adjustments. Then, the problem can be solved by a Dantzig Wolfe decomposition approach including both ship routing subproblems and inventory management subproblems. The overall problem is solved by branch-and-bound. Our computational results indicate that the proposed method works for the real planning problem.

Reliability and heterogeneity of railway services

Reliability is one of the key factors in transportation, both for passengers and for cargo. This paper examines reliability in public railway systems. Reliability of railway services is a complex matter, since there are many causes for disruptions and at least as many causes for delays to spread around in space and time. One way to increase the reliability is to reduce the propagation of delays due to the interdependencies between trains. This paper attempts to decrease these interdependencies by reducing the running time differences per track section, i.e. by creating more homogeneous timetables, as opposed to the present day heterogeneous ones. Because of the complexity of railway systems, the paper uses network wide simulation for the analysis of the alternative timetables. The paper reports on both theoretical and practical cases. Besides a comparison of different timetables, also general timetabling principles are deduced.

Routing Trains through railway stations: model formulation and algorithms

In this paper we consider the problem of routing trains through railway stations. This problem occurs as a subproblem in a project which the authors are carrying out in cooperation with the Dutch railways. The project involves the analysis of future infrastructural capacity requirements in the Dutch railway network. Part of this project is the automatic generation and evaluation of timetables. To generate a timetable a hierarchical approach is followed: at the upper level in the hierarchy a tentative timetable is generated, taking into account the specific scheduling problems of the trains at the railway stations at an aggregate level. At the lower level in the hierarchy it is checked whether the tentative timetable is feasible with respect to the safety rules and the connection requirements at the stations. To carry out this consistency check, detailed schedules for the trains at the railway yards have to be generated. In this paper we present a mathematical model formulation for this detailed scheduling problem, based on the Node Packing Problem (NPP). Furthermore, we describe a solution procedure for the problem, based on a branch-and-cut approach. The approach is tested in an empirical study with data from the station of Zwolle in The Netherlands.

The New Dutch Timetable: The OR Revolution

In December 2006, Netherlands Railways introduced a completely new timetable. Its objective was to facilitate the growth of passenger and freight transport on a highly utilized railway network, and improve the robustness of the timetable resulting in less train delays in the operation. Further adjusting the existing timetable constructed in 1970 was not option anymore, because further growth would then require significant investments in the rail infrastructure. Constructing a railway timetable from scratch for about 5,500 daily trains was a complex problem. To support this process, we generated several timetables using sophisticated operations research techniques, and finally selected and implemented one of these timetables. Furthermore, because rolling-stock and crew costs are principal components of the cost of a passenger railway operator, we used innovative operations research tools to devise efficient schedules for these two resources. The new resource schedules and the increased number of passengers resulted in an additional annual profit of 40 million euros (

Routing trains through a railway station based on a node packing model

60 million) of which about 10 million euros were created by additional revenues. We expect this to increase to 70 million euros (

A rolling stock circulation model for combining and splitting of passenger trains

105 million) annually in the coming years. However, the benefits of the new timetable for the Dutch society as a whole are much greater: more trains are transporting more passengers on the same railway infrastructure, and these trains are arriving and departing on schedule more than they ever have in the past. In addition, the rail transport system will be able to handle future transportation demand growth and thus allow cities to remain accessible. Therefore, people can switch from car transport to rail transport, which will reduce the emission of greenhouse gases.

Disruption Management in Passenger Railway Transportation

In this paper we describe the problem of routing trains through a railway station. This routing problem is a subproblem of the automatic generation of timetables for the Dutch railway system. The problem of routing trains through a railway station is the problem of assigning each of the involved trains to a route through the railway station, given the detailed layout of the railway network within the station and given the arrival and departure times of the trains. When solving this routing problem, several aspects such as capacity, safety, and customer service have to be taken into account. In this paper we describe this routing problem in terms of a Weighted Node Packing Problem. Furthermore, we describe an algorithm for solving this routing problem to optimality. The algorithm is based on preprocessing, valid inequalities, and a branch-and-cut approach. The preprocessing techniques aim at identifying super uous nodes which can be removed from the problem instance. The characteristics of the preprocessing techniques with respect to propagation are investigated. We also present the results of a computational study in which the model, the preprocessing techniques and the algorithm are tested based on data related to the railway stations Arnhem, Hoorn and Utrecht in the Netherlands.

A Variable Trip Time Model for Cyclic Railway Timetabling

This paper addresses the railway rolling stock circulation problem. Given the departure and arrival times as well as the expected numbers of passengers, we have to assign the rolling stock to the timetable services. We consider several objective criteria that are related to operational costs, service quality and reliability of the railway system. Our model is an extension of an existing rolling stock model for routing train units along a number of connected train lines. The extended model can also handle underway combining and splitting of trains. We illustrate our model by computational experiments based on instances of NS Reizigers, the main Dutch operator of passenger trains. � 2005 Elsevier B.V. All rights reserved. Keyword: Railway rolling stock circulation