EconPapers    
Economics at your fingertips  
 

A Mixed Integer Programming Model on the Location of a Hub Port in the East Coast of South America

R Aversa (), R C Botter (), H E Haralambides () and H T Y Yoshizaki ()
Additional contact information
R Aversa: Department of Production Engineering, Polytechnic School, University of São Paulo, Av. Prof. Almeida Prado, Travessa 2, No. 128, Cidade Universitária, São Paulo, SP 05508-900, Brazil.
R C Botter: Department of Naval and Ocean Engineering, Polytechnic School, University of São Paulo, Av. Prof. Mello Moraes, No. 2231, Cidade Universitária, São Paulo, SP 05356-000, Brazil.
H E Haralambides: Center for Maritime Economics and Logistics (MEL), Rotterdam School of Economics, Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands.
H T Y Yoshizaki: Department of Production Engineering, Polytechnic School, University of São Paulo, Av. Prof. Almeida Prado, Travessa 2, No. 128, Cidade Universitária, São Paulo, SP 05508-900, Brazil.

Maritime Economics & Logistics, 2005, vol. 7, issue 1, 18 pages

Abstract: The paper introduces a mixed integer programming model on the selection of a hub port in the East Coast of South America, among a set of 11 ports that are servicing the regional demand for container transportation. Ports in Brazil, Argentina and Uruguay are considered, together with several origin/destination ports in the world. The model minimises total system costs, taking into account both port costs (dues and terminal handling charges) and shipping costs (feedering and mainline). In total, the model consists of 3,883 decision variables and 4,225 constraints. It turns up the port of Santos (Brazil) as the optimal single-hub solution, with the port of Buenos Aires (Argentina) as a close runner up. In addition, the model provides tentative estimates of improvements in demand and costs necessary to bring a certain port up to hub status. Despite some bold assumptions and limitations – mainly due to data availability – the model offers a straightforward decision tool to all ports in the world aspiring to achieve hub status and all that comes with it. Maritime Economics & Logistics (2005) 7, 1–18. doi:10.1057/palgrave.mel.9100121

Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.palgrave-journals.com/mel/journal/v7/n1/pdf/9100121a.pdf Link to full text PDF (application/pdf)
http://www.palgrave-journals.com/mel/journal/v7/n1/full/9100121a.html Link to full text HTML (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:marecl:v:7:y:2005:i:1:p:1-18

Ordering information: This journal article can be ordered from
http://www.springer. ... nt/journal/41278/PS2

Access Statistics for this article

Maritime Economics & Logistics is currently edited by Hercules E. Haralambides

More articles in Maritime Economics & Logistics from Palgrave Macmillan, International Association of Maritime Economists (IAME) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:pal:marecl:v:7:y:2005:i:1:p:1-18