3,769 research outputs found

    Hump Yard Track Allocation with Temporary Car Storage

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    In rail freight operation, freight cars need to be separated and reformed into new trains at hump yards. The classification procedure is complex and hump yards constitute bottlenecks in the rail freight network, often causing outbound trains to be delayed. One of the problems is that planning for the allocation of tracks at hump yards is difficult, given that the planner has limited resources (tracks, shunting engines, etc.) and needs to foresee the future capacity requirements when planning for the current inbound trains. In this paper, we consider the problem of allocating classification tracks in a rail freight hump yard for arriving and departing trains with predetermined arrival and departure times. The core problem can be formulated as a special list coloring problem. We focus on an extension where individual cars can temporarily be stored on a special subset of the tracks. An extension where individual cars can temporarily be stored on a special subset of the tracks is also considered. We model the problem using mixed integer programming, and also propose several heuristics that can quickly give feasible track allocations. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangård hump yard in Sweden. Planning over horizons over two to four days, we obtain feasible solutions from both the exact and heuristic approaches that allow all outgoing trains to leave on time

    Track Allocation in Freight-Train Classification with Mixed Tracks

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    We consider the process of forming outbound trains from cars of inbound trains at rail-freight hump yards. Given the arrival and departure times as well as the composition of the trains, we study the problem of allocating classification tracks to outbound trains such that every outbound train can be built on a separate classification track. We observe that the core problem can be formulated as a special list coloring problem in interval graphs, which is known to be NP-complete. We focus on an extension where individual cars of different trains can temporarily be stored on a special subset of the tracks. This problem induces several new variants of the list-coloring problem, in which the given intervals can be shortened by cutting off a prefix of the interval. We show that in case of uniform and sufficient track lengths, the corresponding coloring problem can be solved in polynomial time, if the goal is to minimize the total cost associated with cutting off prefixes of the intervals. Based on these results, we devise two heuristics as well as an integer program to tackle the problem. As a case study, we consider a real-world problem instance from the Hallsberg Rangerbangård hump yard in Sweden. Planning over horizons of seven days, we obtain feasible solutions from the integer program in all scenarios, and from the heuristics in most scenarios

    Shunting of Passenger Train Units: an Integrated Approach

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    In this paper, we describe a new model for the Train Unit Shunting Problem. This model is capable of solving the matching and parking subproblems in an integrated manner, usually requiring a reasonable amount of computation time for generating acceptable solutions. Furthermore, the model incorporates complicating details from practice, such as trains composed of several train units and tracks that can be approached from two sides. Computation times are reduced by introducing the concept of virtual shunt tracks. Computational results are presented for real-life cases of NS Reizigers, the main Dutch passenger railway operator.Optimization;Passenger Railways;Shunting

    Applying Operations Research techniques to planning of train shunting

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    In this paper, we discuss a model-based algorithmic approach for supporting planners in the creation of shunt plans for passenger trains. The approach provides an example of a mathematical model and a corresponding solution approach for model based support. We introduce a four-step solution approach and we discuss how the planners are supported by this approach. Finally, we present computational results for these steps and give some suggestions for further research.A* search;railway optimization;real world application;routing

    Optimized shunting with mixed-usage tracks

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    We consider the planning of railway freight classification at hump yards, where the problem involves the formation of departing freight train blocks from arriving trains subject to scheduling and capacity constraints. The hump yard layout considered consists of arrival tracks of sufficient length at an arrival yard, a hump, classification tracks of non-uniform and possibly non-sufficient length at a classification yard, and departure tracks of sufficient length. To increase yard capacity, freight cars arriving early can be stored temporarily on specific mixed-usage tracks. The entire hump yard planning process is covered in this paper, and heuristics for arrival and departure track assignment, as well as hump scheduling, have been included to provide the neccessary input data. However, the central problem considered is the classification track allocation problem. This problem has previously been modeled using direct mixed integer programming models, but this approach did not yield lower bounds of sufficient quality to prove optimality. Later attempts focused on a column generation approach based on branch-and-price that could solve problem instances of industrial size. Building upon the column generation approach we introduce a direct arc-based integer programming model, where the arcs are precedence relations between blocks on the same classification track. Further, the most promising models are adapted for rolling-horizon planning. We evaluate the methods on historical data from the Hallsberg shunting yard in Sweden. The results show that the new arc-based model performs as well as the column generation approach. It returns an optimal schedule within the execution time limit for all instances but from one, and executes as fast as the column generation approach. Further, the short execution times of the column generation approach and the arc-indexed model make them suitable for rolling-horizon planning, while the direct mixed integer program proved to be too slow for this. Extended analysis of the results shows that mixing was only required if the maximum number of concurrent trains on the classification yard exceeds 29 (there are 32 available tracks), and that after this point the number of extra car roll-ins increases heavily

    Operations research in passenger railway transportation

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    In this paper, we give an overview of state-of-the-art OperationsResearch models and techniques used in passenger railwaytransportation. For each planning phase (strategic, tactical andoperational), we describe the planning problems arising there anddiscuss some models and algorithms to solve them. We do not onlyconsider classical, well-known topics such as timetabling, rollingstock scheduling and crew scheduling, but we also discuss somerecently developed topics as shunting and reliability oftimetables.Finally, we focus on several practical aspects for each of theseproblems at the largest Dutch railway operator, NS Reizigers.passenger railway transportation;operation research;planning problems

    Working Memory Networks for Learning Temporal Order, with Application to 3-D Visual Object Recognition

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    Working memory neural networks are characterized which encode the invariant temporal order of sequential events. Inputs to the networks, called Sustained Temporal Order REcurrent (STORE) models, may be presented at widely differing speeds, durations, and interstimulus intervals. The STORE temporal order code is designed to enable all emergent groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed in neural architectures which self-organize learned codes for variable-rate speech perception, sensory-motor planning, or 3-D visual object recognition. Using such a working memory, a self-organizing architecture for invariant 3-D visual object recognition is described. The new model is based on the model of Seibert and Waxman (1990a), which builds a 3-D representation of an object from a temporally ordered sequence of its 2-D aspect graphs. The new model, called an ARTSTORE model, consists of the following cascade of processing modules: Invariant Preprocessor --> ART 2 --> STORE Model --> ART 2 --> Outstar Network.Defense Advanced Research Projects Agency (90-0083); British Petroleum (89-A1-1204); National Science Foundation (IRI 90-00530, IRI 87-16960); Air Force Office of Scientific Research (90-128, 90-0175

    Electrical Compartmentalization in Neurons

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    The dendritic tree of neurons plays an important role in information processing in the brain. While it is thought that dendrites require independent subunits to perform most of their computations, it is still not understood how they compartmentalize into functional subunits. Here, we show how these subunits can be deduced from the properties of dendrites. We devised a formalism that links the dendritic arborization to an impedance-based tree graph and show how the topology of this graph reveals independent subunits. This analysis reveals that cooperativity between synapses decreases slowly with increasing electrical separation and thus that few independent subunits coexist. We nevertheless find that balanced inputs or shunting inhibition can modify this topology and increase the number and size of the subunits in a context-dependent manner. We also find that this dynamic recompartmentalization can enable branch-specific learning of stimulus features. Analysis of dendritic patch-clamp recording experiments confirmed our theoretical predictions.Peer reviewe

    Optimisation of simultaneous train formation and car sorting at marshalling yards

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    Efficient and correct freight train marshalling is vital for high quality carload freight transportations. During marshalling, it is desirable that cars are sorted according to their individual drop-off locations in the outbound freight trains. Furthermore, practical limitations such as non-uniform and limited track lengths and the arrival and departure times of trains need to be considered. This paper presents a novel optimisation method for freight marshalling scheduling under these circumstances. The method is based on an integer programming formulation that is solved using column generation and branch and price. The approach minimises the number of extra shunting operations that have to be performed, and is evaluated on real-world data from the Hallsberg marshalling yard in Sweden
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