A multi-phase model to forecast congestion at Brazilian grain ports : a case study at the port of Paranagua

Naude, Jacqueline (2016-03)

Thesis (MComm)—Stellenbosch University, 2016.

Thesis

ENGLISH ABSTRACT: Port congestion occurs when the number of vessels arriving at a port within a given time frame exceeds the number of vessels that can be served during that time frame. At Brazilian grain ports, congestion has increased over the past decade due to an acceleration in trade volumes amidst limited expansion in port infrastructure. Extensive and unforeseen delays have highlighted the need to develop a forecasting model to estimate future levels of congestion in terms of queue lengths and waiting times based on the anticipated volume of grains to be exported. The complexity of the required model is intensified by the seasonal variation in the grain trade, the evolvement of port capacity, and external events such as weather related delays. The Port of Paranagua is chosen as case study. A multi-phase congestion model (MPCM) is proposed comprising five individual yet interdependent phases. This step-wise approach translates the forecasted volume of annual Brazilian grain exports into the anticipated monthly number of vessels waiting at the Port of Paranagua, as well as the corresponding average duration of the waiting periods. The methods applied by the MPCM to achieve these outcomes include linear programming, time-series forecasting, Monte Carlo simulation and multiple regression. Input data between January 2011 and December 2013 are used to forecast monthly congestion for a hold-out period ranging from January to December 2014, as well as a long term forecast period ranging between January 2015 and December 2016. For the Port of Paranagua, the results generated by the MPCM indicate an overall decline in congestion levels for 2015 and 2016. The performance of the MPCM is validated by comparing the estimated values of the hold-out period to actual recorded congestion levels, and by applying the methodology to another port in the Brazilian grain network. The results obtained would be of value to both vessel owners and charterers to hedge their positions, and would give owners the opportunity to strategically position their vessels for optimal utilisation. The proposed methodology can serve as basis for future development to generate a conglomerate view of congestion levels in the Brazilian port network.

AFRIKAANSE OPSOMMING: Hawekongestie vind plaas wanneer die aantal aankomste oor ’n gespesifiseerde tydperk die dienskapasiteit van die tydperk oorskry. Brasiliaanse graanuitvoere het drasties oor die afgelope dekade toegeneem terwyl hawe kapasiteit nie teen dieselfde tempo uitgebrei het nie. Die wanbalans het ernstige bottelnekke veroorsaak wat tot langdurige en onverwagse wagperiodes gelei het. n Vooruitskattingsmodel is dus nodig wat toekomstige toue en wagtye by die relevante hawens kan bereken met behulp van die verwagte volumes wat uitgevoer gaan word. Die kompleksiteit van die vereiste model lê in die seisoenale variasie in graanuitvoere, veranderinge in handelspatrone, uitbreidings in hawe infrastruktuur en onverwagse eksterne gebeurtenisse soos weerverwante vertragings. Paranagua is gekies as gevallestudie. In hierdie tesis word ’n Multi-fase kongestiemodel (MFKM) voorgestel wat uit vyf individuele, maar tog interafhanklike fases bestaan. Die MFKM neem die totale van die verwagte jaarlikse graanuitvoere vanuit Brasilië, en transformeer dit stapsgewys na die verwagte aantal skepe wat per maand by Paranagua wag, asook die gemiddelde wagtyd van hierdie skepe. Ten einde hierdie doel te bereik, word liniêre programmering, ’n tydreeks vooruitskattingsmetode, meervoudige regressie en Monte Carlo simulasie in verskillende fases aangewend. Invoerdata tussen Januarie 2011 en Desember 2013 is gebruik om maanderlikse kongestie vanaf Januarie tot Desember 2014 vooruit te skat. Die resultate van die MFKM wys op ’n algehele daling in kongestievlakke by Paranagua vir 2015 en 2016. Die akkuraatheid van die resultate word gevalideer deur die berekende waardes te vergelyk met die werklike gepubliseerde waardes in 2014, asook deur die model op ’n alternatiewe hawe in the Brasiliaanse graanhawenetwerk toe te pas. Die resultate is van waarde vir skeepseienaars en skeepshuurders omdat dit insig verleen tot die verwagte beskikbaarheid van skepe in die relevante area asook die verwagte tyd wat die skepe gaan moet wag om ’n vrag te laai. Die model kan gebruik word as basis vir verdere ontwikkeling deur die metodologie te dupliseer op ander hawens in die Brasiliaanse graannetwerk en sodoende ’n oorkoepelende kongestievooruitskatting te verwesenlik.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/98848
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