Robustness for a single railway line: Analytical and simulation methods

[EN] Railway scheduling has been a significant issue in the railway industry. Over the last few years, numerous approaches and tools have been developed to compute railway scheduling. However, robust solutions are necessary to absorb short disruptions. In this paper, we present the robustness problem from the point of view of railway operators and we propose analytical and simulation methods to measure robustness in a single railway line. In the analytical approach, we have developed some formulas to measure robustness based on the study of railway line infrastructure topology and buffer times. In the simulation approach, we have developed a software tool to assess the robustness for a given schedule. These methods have been inserted in MOM (More information can be found at the MOM web page http://www.dsic.upv.es/users/ia/gps/MOM), which is a project in collaboration with the Spanish Railway Infrastructure Manager (ADIF). © 2012 Elsevier Ltd. All rights reserved.This work has been partially supported by the research project TIN2010-20976-C02-01 (Min. de Economia y Competitividad, Spain) and project PIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES).Salido Gregorio, MA.; Barber Sanchís, F.; Ingolotti Hetter, LP. (2012). Robustness for a single railway line: Analytical and simulation methods. Expert Systems with Applications. 39(18):13305-13327. https://doi.org/10.1016/j.eswa.2012.05.071S1330513327391

AI and OR in management of operations: history and trends

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Planning and scheduling activities within the rail industry have benefited from developments in computer-based simulation and modelling techniques over the last 25 years. Increasingly, the use of computational intelligence in such tasks is featuring more heavily in research publications. This paper examines a number of common rail-based planning and scheduling activities and how they benefit from five broad technology approaches. Summary tables of papers are provided relating to rail planning and scheduling activities and to the use of expert and decision systems in the rail industry.EPSR

Human-Machine Collaborative Optimization via Apprenticeship Scheduling

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