Large Scale Railway Renewal Planning with a Multiobjective Modeling Approach

Authors Nuno Sousa , Luis Alçada-Almeida , João Coutinho-Rodrigues



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Nuno Sousa
  • INESC-Coimbra, Coimbra, Portugal, Department of Sciences and Technology, Open University, Lisbon, Portugal, R. da Escola Politécnica 141-147, 1269-001 Lisboa, Portugal. Phone +351 213 916 300
Luis Alçada-Almeida
  • INESC-Coimbra, Coimbra, Portugal , Faculty of Economics, University of Coimbra, Coimbra, Portugal, Av. Dr. Dias da Silva 165, 3004-512 Coimbra, Portugal. Phone: +351 239 790 500
João Coutinho-Rodrigues
  • INESC-Coimbra, Coimbra, Portugal, Department of Civil Engineering, Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal, Rua Luís Reis Santos - Polo II, 3030-788 Coimbra, Portugal. Phone +351 239 797 100

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Nuno Sousa, Luis Alçada-Almeida, and João Coutinho-Rodrigues. Large Scale Railway Renewal Planning with a Multiobjective Modeling Approach. In 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018). Open Access Series in Informatics (OASIcs), Volume 65, pp. 2:1-2:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/OASIcs.ATMOS.2018.2

Abstract

A multiobjective modeling approach for managing large scale railway infrastructure asset renewal is presented. An optimized intervention project schedule is obtained considering operational constraints in a three objectives model: evenly spreading investment throughout multiple years, minimizing total cost, minimizing work start postponements on higher priority railway sections. The MILP model was based on a real world case study; the objectives and constraints specified by an infrastructure management company. Results show that investment spreading greatly influences the other objectives and that total cost fluctuations depend on the overall condition of the railway infrastructure. The model can produce exact efficient solutions in reasonable time, even for very large-sized instances (a test network of similar size to the USA railway network, the largest in the world). The modeling approach is therefore a very useful, practical methodology, for generating optimized solutions and analyzing trade-offs among objectives, easing the task of ultimately selecting a solution and produce the works schedule for field implementation.

Subject Classification

ACM Subject Classification
  • Theory of computation → Integer programming
Keywords
  • Rail infrastructure
  • Renewal maintenance
  • Multiobjective modeling

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References

  1. António R. Andrade and Paulo F. Teixeira. Biobjective optimization model for maintenance and renewal decisions related to rail track geometry. Transportation Research Record: Journal of the Transportation Research Board, 2261:163-170, 2011. URL: http://dx.doi.org/10.3141/2261-19.
  2. David Banister and Mark Thurstain-Goodwin. Quantification of the non-transport benefits resulting from rail investment. Journal of Transport Geography, 19(2):212-223, 2011. URL: http://dx.doi.org/10.1016/j.jtrangeo.2010.05.001.
  3. Lucio Bianco, Massimiliano Caramia, and Stefano Giordani. Resource levelling in project scheduling with generalized precedence relationships and variable execution intensities. OR Spectrum, 32(2):405-425, 2016. URL: http://dx.doi.org/10.1007/s00291-016-0435-1.
  4. Gabriella Budai, Dennis Huisman, and Rommert Dekker. Scheduling preventive railway maintenance activities. Journal of the Operational Research Society, 57(9):1035-1044, 2006. URL: http://dx.doi.org/10.1057/palgrave.jors.2602085.
  5. Marc Gaudry, Bernard Lapeyre, and Émile Quinet. Infrastructure maintenance, regeneration and service quality economics: A rail example. Transportation Research Part B: Methodological, 86:181-210, 2016. URL: http://dx.doi.org/10.1016/j.trb.2016.01.015.
  6. IMPROVERAIL. Deliverable 10: Project handbook. improved tools for railway capacity and access management, 2003. URL: http://www.transport-research.info/sites/default/files/project/documents/20060727_145926_44007_IMPROVERAIL_Final_Report.pdf.
  7. RailNetEurope. Glossary of terms related to railway network statements, 2016. URL: http://www.rne.eu/rneinhalt/uploads/RNE_NetworkStatementGlossary__V8_2016_web.pdf.
  8. Julia Rieck, Juergen Zimmermann, and Thorsten Gather. Mixed-integer linear programming for resource leveling problems. European Journal of Operational Research, 221(1):27-37, 2012. URL: http://dx.doi.org/10.1016/j.ejor.2012.03.003.
  9. René Schenkendorf, Joern C. Groos, and Lars Johannes. Strengthening the rail mode of transport by condition based preventive maintenance. IFAC-PapersOnLine, 48(21):964-969, 2015. 9th IFAC Symposium on Fault Detection, Supervision andSafety for Technical Processes SAFEPROCESS 2015. URL: http://dx.doi.org/10.1016/j.ifacol.2015.09.651.
  10. Statista. Length of railroad network in selected countries around the world as of 2015, 2018. URL: https://www.statista.com/statistics/264657/ranking-of-the-top-20-countries-by-length-of-railroad-network.
  11. Sander van Aken, Nikola Bešinović, and Rob M.P. Goverde. Designing alternative railway timetables under infrastructure maintenance possessions. Transportation Research Part B: Methodological, 98:224-238, 2017. URL: http://dx.doi.org/10.1016/j.trb.2016.12.019.
  12. Min Wen, Rui Li, and Kim B. Salling. Optimization of preventive condition-based tamping for railway tracks. European Journal of Operational Research, 252(2):455-465, 2016. URL: http://dx.doi.org/10.1016/j.ejor.2016.01.024.
  13. Allan Woodburn. An analysis of rail freight operational efficiency and mode share in the british port-hinterland container market. Transportation Research Part D: Transport and Environment, 51:190-202, 2017. URL: http://dx.doi.org/10.1016/j.trd.2017.01.002.
  14. Zhang Xueqing and Gao Hui. Determining an optimal maintenance period for infrastructure systems. Computer-Aided Civil and Infrastructure Engineering, 27(7):543-554, 2012. URL: http://dx.doi.org/10.1111/j.1467-8667.2011.00739.x.
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