Titlebook: Computer-aided Systems in Public Transport; Mark Hickman,Pitu Mirchandani,Stefan Voß Conference proceedings 2008 Springer-Verlag Berlin He

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,“Rome, etc.”: ,, and the Prodigious City,sons Rail have developed scheduling software that can generate optimised train plans automatically. The system takes a description of the way trains move through the network and a list of trains that are required to run, and quickly generates a train plan that is optimised against key performance in

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Early Modern Cultural Studies 1500–1700he target running time, and vice versa. The autoregressive model specifies the upcoming running time as a function of the most recent running time. This model characterizes one of two situations depending on the sign of the parameter estimate. On the one hand, when the most recent running time is lo

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Early Modern Cultural Studies 1500–1700e control strategy when in-vehicle time is not considered. When accounting for in-vehicle delay, the optimal holding strategy consists of only a few trains being held at a few stations. Overall, the results suggest the present formulation yields control strategies that are simple enough to be implem

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A Bundle Method for Integrated Multi-Depot Vehicle and Duty Scheduling in Public Transitach is based on a version of the proximal bundle method for the solution of concave decomposable functions that is adapted for the approximate evaluation of the vehicle and duty scheduling components. The primal and dual information generated by this bundle method is used to guide a branch-and-bound

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A Crew Scheduling Approach for Public Transit Enhanced with Aspects from Vehicle Schedulinging vehicle scheduling problem. We use a model of the vehicle scheduling problem which is based on a time-space network formulation. An advantage of this procedure is that it produces a bundle of optimal vehicle schedules, implicitly given by the solution flow. In our approach, we give this degree o

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Line Change Considerations Within a Time-Space Network Based Multi-Depot Bus Scheduling Modelips. It considers additional requirements, such as multiple depots for vehicles and vehicle type groups for timetabled trips as well as depot capacities. An optimal schedule is characterized by minimal fleet size and minimal operational costs including costs for unloaded trips and idle time spent ou