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Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

handle: 11588/725331
AbstractThe paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown.
travel demand, rail systems; simulation; optimisation; travel demand; energy-saving; metaheuristic techniques., TA1001-1280, Metaheuristic techniques, optimisation, Rail systems, simulation, Travel demand, Transportation engineering, metaheuristic techniques, rail systems, Energy saving, energy-saving, Optimisation, Transportation and communications, Simulation, HE1-9990
travel demand, rail systems; simulation; optimisation; travel demand; energy-saving; metaheuristic techniques., TA1001-1280, Metaheuristic techniques, optimisation, Rail systems, simulation, Travel demand, Transportation engineering, metaheuristic techniques, rail systems, Energy saving, energy-saving, Optimisation, Transportation and communications, Simulation, HE1-9990
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).29 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 2 download downloads 1 - 2views1downloads
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