Abstract
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.
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Baird, AJ (2003) UK marine motorways study: summary final report. Engineering and Physical Sciences Research Council (EPSRC) and the Department of Transportation (DfT)
BOE No. 92 (2006) Boletín oficial del estado español no 265. Bases reguladoras de las Autopistas del mar entre España y Francia
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. 1–8
Daganzo CF (2005) Many-To-Many distribution. In: Logistics systems analysis. Springer, Berlin, 215–268
Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Hjelle HM (2010) Short sea shipping’s green label at risk. Trans Rev 30(5):617–640
Hjelle HM, Fridell E (2012) When is short sea shipping environmentally competitive? In: Environmental health-emerging issues and practice. IntechOpen, London
Jiang L, Kronbak J (2012) The model of maritime external costs, University of Southern Denmark, Project no. 2010-56, Emissionsbeslutningsstøttesystem. Work package 1
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 28:19–27
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-MOVE
Kristensen HO (2012) Energy demand and exhaust gas emissions of marine engines. Clean Shipp Curr 1(6):18–26
Lützen M, Kristensen, HOH (2012) A model for prediction of propulsion power and emissions–tankers and bulk carriers. In: World maritime technology conference, Saint-Petersburg
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 Delft
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):494–520
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):89–113
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):608–631
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):653–686
Medda F, Trujillo L (2010) Short-sea shipping: an analysis of its determinants. Marit Policy Manag 37(3):285–303
Ntziachristos L, Samaras Z (2012) Exhaust emissions for road transport-EMEP/EEA Emission inventory guidebook 2009. European Environment Agency, Copenhagen
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):451–471
Project, SPIN-HSV (2003–2005) Shipping quality and safety of high speed vessels (Deliverable D5.8, Public Summary Report of Work Package \(no 5\))
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 mundo
Suárez-Alemán A, Trujillo L, Cullinane KPB (2014) Time at ports in short sea shipping: when timing is crucial. Marit Econ Logist 16(4):399–417
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):317–334
Zitzler E, Deb K, Thiele L (2000) Comparison of multiobjective evolutionary algorithms: empirical results. Evol Comput 8(2):173–195
Acknowledgements
This work was funded by the Inter-American Development Bank (IDB). The authors, therefore, acknowledge with thanks IDB technical and financial support.
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Appendix
Appendix
Subscripts:
- \(BB=\left\{ 1,\ldots ,b\right\} \):
-
Decisions on the installation of bow thrusters in vessels: without and with bow thrusters
- \(DD=\left\{ 1,\ldots ,d\right\} \):
-
Destinations in land (nodes) for the transport network: Iquique, Antofagasta and La Serena in the north; Concepción and Temuco in the south
- \(EE=\left\{ 1,\ldots ,e\right\} \):
-
Group of types of main engines: diesel engine and turbines \(GG=\left\{ 1,\ldots ,g\right\} \) Alternatives for cargo-handling systems: crane vessels and port cranes
- \(H=\left\{ 1,\ldots ,h\right\} \):
-
Possible kind of propeller: conventional skew or waterjet
- \(I=\left\{ 1,\ldots ,i\right\} \):
-
Number of main engines (from 1 to 4)
- \(J=\left\{ 1,\ldots ,j\right\} \):
-
Direction of transport (north–south and south–north)
- \(K=\left\{ 1,\ldots ,k\right\} \):
-
Peripheral ports: Arica, Iquique, Mejillones and Antofagasta in the north; San Vicente and Coronel in the south
- \(M=\left\{ 1,\ldots ,m\right\} \):
-
Large-scale hub ports: Valparaiso and San Antonio
- \(N=\left\{ 1,\ldots ,n\right\} \):
-
Number of shaft lines in the machine room (from 1 to 4)
- \(PP=\left\{ 1,\ldots ,p\right\} \):
-
Kinds of cargo units for container vessels: TEUs and FEUs \(Q=\left\{ 1,\ldots ,q\right\} \) Group of possible ages for the fleet: 1, 6 and 14 years
- \(U=\left\{ 1,\ldots ,u\right\} \):
-
Group of evaluated pollutants: \(SO_{2}\), \(NO_{x}\), \(PM_{2.5}\) and \(CO_{2}\)
- \(Z=\left\{ 1,\ldots ,z\right\} \):
-
Land origins (central nodes) for the transport network: Santiago, Valparaíso, hub port (Valparaiso or San Antonio), La Serena and Rancagua
Superscripts:
- \(MTA=\left\{ a,b\right\} \):
-
Modal alternatives for the transport: road haulage and intermodality, respectively.
- \(ST=\left\{ c\right\} \):
-
The MoS evaluated: MoS North and MoS South.
- \(DIS=\left\{ d\right\} \):
-
Obligatory to have two drivers in the truck (No; Yes)
Variables:
- \(CK_{dp}\):
-
Unitary costs for road haulage with one driver (TEUs and FEUs: \(CK11=0.27/km\), \(CK12=0.44/km\)) and with two drivers (TEUs and FEUs: \(CK21=0.32 /km\), \(CK22=0.53 /km\))
- \(DM_{mk}\):
-
Maritime distance of the route (km): \(\forall m\in M\bigwedge \forall k\in K\)
- \(DRa_{zd}\):
-
Land distance for the unimodal alternative (km): \(\forall z\in Z\bigwedge \forall d\in DD\)
- \(DRb_{zm}\):
-
Distances of the capillary hauls for the intermodal chains from/to peripheral ports (km): \(\forall z\in Z\bigwedge \forall m\in M\)
- \(DRb_{kd}\):
-
Distances of the capillary hauls for the intermodal chains from/to large-scale hub ports (km): \(\forall k\in K\bigwedge \forall d\in DD\)
- \(E_{q}\):
-
Age of the vessel from time of building: \(\forall q\in Q\)
- \(G_{p}\):
-
Cargo capacity of the vessel in units: \(\forall p\in PP\)
- \(MG_{g}\):
-
Cargo-handling systems: \(\forall g\in GG\)
- \(MM_{b}\):
-
Manoeuvring means for the vessels (bow thruster): \(\forall b\in BB\)
- \(N_{trips}\):
-
Yearly number of trips for the fleet
- \(NME_{i}\):
-
Number of main engines of the vessel: \(\forall i\in I\)
- \(NMG_{k}\):
-
Maximum number of cranes for the peripheral port: \(\forall k\in K\)
- \(NMG_{m}\):
-
Maximum number of cranes for the large-scale hub port: \(\forall m\in M\)
- \(NSL_{n}\):
-
Number of shaft lines in a vessel: \(\forall n\in N\)
- \(P_{p}\):
-
Weigh of the cargo units (t): \(\forall p\in PP\)
- \(TME_{e}\):
-
Type of main engine for the vessels: \(\forall e\in EE\)
- \(TP_{h}\):
-
Type of propulsion for the vessels: \(\forall h\in H\)
- VB:
-
Speed of the vessel (Kn)
- \(X_{d}\):
-
Relative probability of cargo delivery in a node with respect to the other possible nodes in the north and in the south (%): \(\forall d\in DD\)
- \(Xc_{jz}\):
-
Relative probability of cargo delivery in a node with respect to the other possible nodes in the centre for every MoS and in each direction (%):\(\forall z\in Z\bigwedge \forall c\in ST\bigwedge \forall j\in J\)
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Martínez-López, A., Lourdes, T., González Manuel, C. (2020). Establishment of MoS in Chile: Pertinence Assessment Through an Analysis of Previous Scenarios. In: Diez, P., Neittaanmäki, P., Periaux, J., Tuovinen, T., Pons-Prats, J. (eds) Computation and Big Data for Transport. Computational Methods in Applied Sciences, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-030-37752-6_11
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