Establishment of MoS in Chile: Pertinence Assessment Through an Analysis of Previous Scenarios

Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 54)


With the opening of the Panama Canal, Chile is adapting its transport logistics to the expected arrival of larger container vessels by assuming the establishment of a hub port in its central region. This paper tackles the feasibility of the intermodal chains through MoS to feed the North and the South regions from this central hub port. Due to the features of Chile, the intermodal distances are similar to the unimodal distances. This fact along with the remarkable imbalance of the cargo flows between the North and the South are an additional challenge for the success of the intermodality. In order to support the opportunities of success of the intermodality this study defines, through the optimization of a mathematical model, the most adequate fleets for MoS in the North and South of Chile. Likewise, assuming identical conditions for all Chilean ports (previous scenarios), the resolution of the model identifies the most suitable peripheral ports to articulate MoS from a large-scale hub port in the central region of Chile. The results show that, the intermodality is a competitive solution in the north, but it is not in the south when optimized fleets are used.


Short sea shipping Motorways of the sea Intermodal chains Multi-objective optimization Evolutionary algorithms 



This work was funded by the Inter-American Development Bank (IDB). The authors, therefore, acknowledge with thanks IDB technical and financial support.


  1. 1.
    Baird, AJ (2003) UK marine motorways study: summary final report. Engineering and Physical Sciences Research Council (EPSRC) and the Department of Transportation (DfT)Google Scholar
  2. 2.
    BOE No. 92 (2006) Boletín oficial del estado español no 265. Bases reguladoras de las Autopistas del mar entre España y FranciaGoogle Scholar
  3. 3.
    Caamaño P, Tedín R, Paz-Lopez A, Becerra JA (2010) Jeaf: a java evolutionary algorithm framework. In: IEEE congress on evolutionary computation. IEEE, Barcelona, pp. 1–8Google Scholar
  4. 4.
    Daganzo CF (2005) Many-To-Many distribution. In: Logistics systems analysis. Springer, Berlin, 215–268Google Scholar
  5. 5.
    Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197CrossRefGoogle Scholar
  6. 6.
    Hjelle HM (2010) Short sea shipping’s green label at risk. Trans Rev 30(5):617–640CrossRefGoogle Scholar
  7. 7.
    Hjelle HM, Fridell E (2012) When is short sea shipping environmentally competitive? In: Environmental health-emerging issues and practice. IntechOpen, LondonGoogle Scholar
  8. 8.
    Jiang L, Kronbak J (2012) The model of maritime external costs, University of Southern Denmark, Project no. 2010-56, Emissionsbeslutningsstøttesystem. Work package 1Google Scholar
  9. 9.
    Jiang L, Kronbak J, Christensen LP (2014) The costs and benefits of sulphur reduction measures: sulphur scrubbers versus marine gas oil. Trans Res Part D: Trans Environ 28:19–27CrossRefGoogle Scholar
  10. 10.
    Korzhenevych A, Dehnen N, Broecker J, Holtkamp M, Meier H, Gibson G, Varma A, Cox V (2014) Update of the handbook on external costs of transport: final report for the European Commission: DG-MOVEGoogle Scholar
  11. 11.
    Kristensen HO (2012) Energy demand and exhaust gas emissions of marine engines. Clean Shipp Curr 1(6):18–26Google Scholar
  12. 12.
    Lützen M, Kristensen, HOH (2012) A model for prediction of propulsion power and emissions–tankers and bulk carriers. In: World maritime technology conference, Saint-PetersburgGoogle Scholar
  13. 13.
    Maibach M, Schreyer C, Sutter D, Van Essen HP, Boon BH, Smokers R, Schroten A, Doll C, Pawlowska B, Bak M (2008) Handbook on estimation of external costs in the transport sector. Ce DelftGoogle Scholar
  14. 14.
    Martínez-Lopez A, Kronbak J, Jiang L (2015) Cost and time models for the evaluation of intermodal chains by using short sea shipping in the North Sea region: the Rosyth-Zeebrugge route. Int J Shipp Transp Logist 7(4):494–520Google Scholar
  15. 15.
    Martínez-López A, Sobrino PC, Santos LC (2015) Definition of optimal fleets for Sea Motorways: the case of France and Spain on the Atlantic coast. Int J Shipp Transp Logist 7(1):89–113CrossRefGoogle Scholar
  16. 16.
    Martínez-López A, Munín-Doce A, García-Alonso L (2015) A multi-criteria decision method for the analysis of the Motorways of the Sea: the application to the case of France and Spain on the Atlantic Coast. Marit Policy Manag 42(6):608–631CrossRefGoogle Scholar
  17. 17.
    Martínez-López A, Sobrino PC, González MM (2016) Influence of external costs on the optimisation of container fleets by operating under motorways of the sea conditions. Int J Shipp Transp Logist 8(6):653–686CrossRefGoogle Scholar
  18. 18.
    Medda F, Trujillo L (2010) Short-sea shipping: an analysis of its determinants. Marit Policy Manag 37(3):285–303CrossRefGoogle Scholar
  19. 19.
    Ntziachristos L, Samaras Z (2012) Exhaust emissions for road transport-EMEP/EEA Emission inventory guidebook 2009. European Environment Agency, CopenhagenGoogle Scholar
  20. 20.
    Pérez-Mesa JC, Céspedes-Lorente JJ, Andújar JAS (2010) Feasibility study for a Motorway of the Sea (MoS) between Spain and France: application to the transportation of perishable cargo. Transp Rev 30(4):451–471CrossRefGoogle Scholar
  21. 21.
    Project, SPIN-HSV (2003–2005) Shipping quality and safety of high speed vessels (Deliverable D5.8, Public Summary Report of Work Package \(no 5\))Google Scholar
  22. 22.
    Sabonge R, Lugo E, et al (2014) Diagnóstico y pronóstico sobre la oferta y demanda de servicios de transporte marítimo de naves de línea regular, entre Chile y el mundoGoogle Scholar
  23. 23.
    Suárez-Alemán A, Trujillo L, Cullinane KPB (2014) Time at ports in short sea shipping: when timing is crucial. Marit Econ Logist 16(4):399–417CrossRefGoogle Scholar
  24. 24.
    Suárez-Alemán A, Trujillo L, Medda F (2015) Short sea shipping as intermodal competitor: a theoretical analysis of European transport policies. Marit Econ Logist 42(4):317–334CrossRefGoogle Scholar
  25. 25.
    Zitzler E, Deb K, Thiele L (2000) Comparison of multiobjective evolutionary algorithms: empirical results. Evol Comput 8(2):173–195CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mechanical Engineering (Naval Architecture unit), University School of Civil and Industrial Engineering (Campus of Tafira)University of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain
  2. 2.Department Applied Economics, Faculty of Economics (Campus of Tafira)University of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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