Sara Gestrelius

Maintaining tracks and traffic flow at the same time

In an ideal world, all railway tracks would be available to trains at all times. In reality, track sections need to be closed every now and again for track maintenance and upgrades in order to ensure a satisfactory level of safety and comfort. In this paper, we present a MIP model that optimizes a production plan with regard to both trains and preventive maintenance. The planned maintenance activities may not be canceled, but may be moved in time within pre-defined time windows. Trains may be moved in time, redirected to other parts of the geography, or even canceled. The goal for the optimization is to find the best possible traffic flow given a fixed set of planned maintenance activities. In addition to presenting the model, we discuss the current maintenance planning process in Sweden, and exemplify the usefulness of our model in practice by applying it to two typical scenarios.

Optimal Freight Train Classification using Column Generation

We consider planning of freight train classification at hump yards using integer programming. The problem involves the formation of departing freight trains from arriving trains subject to scheduling and capacity constraints. To increase yard capacity, we allow the temporary storage of early freight cars on specific mixed-usage tracks. The problem has previously been modeled using a direct integer programming model, but this approach did not yield lower bounds of sufficient quality to prove optimality. In this paper, we formulate a new extended integer programming model and design a column generation approach based on branch-and-price to solve problem instances of industrial size. We evaluate the method on historical data from the Hallsberg hump yard in Sweden, and compare the results with previous approaches. The new method managed to find optimal solutions in all of the 192 problem instances tried. Furthermore, no instance took more than 13 minutes to solve to optimality using fairly standard computer hardware.

Using timetabling optimization prototype tools in new ways to support decision making

The Swedish infrastructure manager Trafikverket is funding research for timetabling optimization tools as part of their overall mission to utilize the existing infrastructure more efficiently. Currently, Trafikverket is modernizing both planning processes and the IT architecture, and will soon be ready to start using optimization tools on a broad scale. Meanwhile, innovative uses of a prototype developed at SICS have shown how a prototype does not necessarily merely serve to pave way for a future, large-scale implementation. This paper shows how computers in railway planning, coupled with OR techniques, relevant data and apt modeling, can help provide a future user with valuable insights even before the full-fledged tool is in place.

Optimization Methods for Multistage Freight Train Formation

This paper considers mathematical optimization for the multistage train formation problem, which at the core is the allocation of classification yard formation tracks to outbound freight trains, subject to realistic constraints on train scheduling, arrival and departure timeliness, and track capacity. The problem formulation allows the temporary storage of freight cars on a dedicated mixed-usage track. This real-world practice increases the capacity of the yard, measured in the number of simultaneous trains that can be successfully handled. Two optimization models are proposed and evaluated for the multistage train formation problem. The first one is a column-based integer programming model, which is solved using branch and price. The second model is a simplified reformulation of the first model as an arc-indexed integer linear program, which has the same linear programming relaxation as the first model. Both models are adapted for rolling horizon planning and evaluated on a five-month historical data set from the largest freight yard in Scandinavia. From this data set, 784 instances of different types and lengths, spanning from two to five days, were created. In contrast to earlier approaches, all instances could be solved to optimality using the two models. In the experiments, the arc-indexed model proved optimality on average twice as fast as the column-based model for the independent instances, and three times faster for the rolling horizon instances. For the arc-indexed model, the average solution time for a reasonably sized planning horizon of three days was 16 seconds. Regardless of size, no instance took longer than eight minutes to be solved. The results indicate that optimization approaches are suitable alternatives for scheduling and track allocation at classification yards.

A Distributed Spatio-Temporal Event Correlation Protocol for Multi-Layer Virtual Networks

We present a distributed spatio-temporal event correlation protocol for multi-layer networks. The problems that we address relate to scalability in stacked overlay networks and network equipment with asynchronous clocks, which complicates the problem of event correlation. We describe a cross-layer protocol designed to address these problems, operating in a fully distributed manner and taking into account asynchronous timestamps. It is assumed that events in one layer may arise from a series of events in lower layers. Detected events that are spatially related in one layer are aggregated using a gossip-like protocol, and constitute a root cause. The set of aggregated events is disseminated to lower layers and used for temporal correlation. We have tested the scalability and the performance of the distributed event protocol, using both synthetically generated and real-world topologies. The results indicate that the average overhead produced for collecting events down the stack of overlays increases with the number of layers. For a fixed number of layers, the protocol scales similarly with the graph-theoretic properties for a network of increasing size.

Towards shorter lead times in railway timetabling in Sweden

Railway timetabling in Sweden has traditionally been associated with long lead times. In order for the railway sector to be able to compete with other transport modes, the infrastructure manager must become better at meeting the demand for railway services whose need for infrastructure capacity is not well-defined 6-18 months in advance. Research at SICS is changing the Swedish timetabling process so that it will accommodate late capacity requests in a significantly better way than before. This paper describes the principle behind the new method, briefly describes the optimization model that has been developed to support the new process, and presents examples that show how optimization tools can support the new process.

Towards a comprehensive model for track allocation and roll-time scheduling at marshalling yards☆

This paper considers multi-stage train formation with mixed usage tracks at a marshalling yard without departure yard. A novel integer programming model for scheduling shunting tasks as well as allocating arrival yard tracks and classification bowl tracks is presented. By taking a comprehensive view of the marshalling yard operations, more effective schedules can be found, and a variety of characteristics can be optimised, including shunting work effort, number or cost of tracks, and shunting task start times. Two different objective functions are evaluated: minimising work effort in terms of wagon pull-backs and minimising track costs. A procedure for finding a hot-start solution with few wagon pull-backs is also presented. The proposed model is tested on real data from Savenas marshalling yard in Sweden. The results show that the method is able to return an optimal schedule for a planning period of 4 days if the hot-start solution is optimal or the remaining problem is tractable for the heuristics in CPLEX.