Abstract

Maritime transport covers the immense majority of the world’s international trade, particularly for Spain, where it represents a 74% of the total transported goods. Most of this transport is made via containers, because of its versatility. Its drawback is that very specific infrastructure and large spaces are needed for its management, and these are not fast to build nor cheap. In addition, the inability to manage containers if the infrastructure is under work or has reached his maximum capacity may translate into important economic losses. To prevent this from happening it is mandatory to plan in advance, and that means accept some predictions of the future to act accordingly. There is a wide range of accepted forecasting methods, because none is good in every situation, and predicting container throughput is not an exception. In this project, we will discuss the validity of Markov Chains when it comes to forecast maritime goods exchange, more precisely the total annual volume of TEUs. As real cases, we will take the data of 4 important Spanish ports (Algeciras, Barcelona, Tarragona and Valencia) from 1973 to 2015 and use it to create a prediction model. We will use the Markov property to create predictions and carry out Monte Carlo simulations to sample them. Over the sections we will change the input data and the parameters of the model to better understand the behavior of Markov chains when applied in such area. To have a reference, we will perform a witness forecast by means of a linear regression. An accuracy measure is planned for each of the models to assess a comparison between them, and find which one is more precise, and thus more valid. El transporte marítimo abarca la inmensa mayoría del comercio internacional en todo el mundo, y para España en particular, donde representa el 74% del total transportado. La mayor parte de este transporte se realiza en contenedores, por lo versátiles que resultan. Lo malo de este sistema es que se necesita una infraestructura específica y mucho espacio para poder procesarlos, lo cual tarda tiempo en construirse e implica grandes inversiones. Además, el hecho de no poder recibir contenedores por remodelaciones en la infraestructura o esta ha llegado a su máximo puede traducirse en cuantiosas pérdidas económicas. Para evitar que esto ocurra es de vital importancia planear de antemano, lo cual implica aceptar una predicción y actuar en consecuencia. Existe un amplio abanico de métodos predictivos, esto se debe a que ninguno de ellos es válido en todas las situaciones posibles, y en el ámbito del transporte marítimo no es una excepción. En este Proyecto discutiremos la validez de las cadenas de Márkov a la hora de prever el intercambio de mercancías por vía marítima, más concretamente el número total de TEUs por año. Como estudiar casos reales tomaremos los datos de 4 importantes puertos españoles (Algeciras, Barcelona, Tarragona and Valencia) desde 1973 hasta 2015 y los utilizaremos para probar el modelo. Utilizaremos la propiedad de Márkov para crear las predicciones y llevaremos a cabo simulaciones Monte Carlo con el fin de muestrearlas. A través de los diferentes apartados iremos cambiando los datos y los parámetros del modelo para entender mejor el comportamiento de las cadenas de Márkov cuando se aplican en esta área en particular. Para tener una referencia, utilizaremos como experimento testigo una predicción realizada con una regresión lineal. Está planeada también una medida de la precisión de cada uno de los modelos, para poder así compararlos y evaluar cuál es el que mejor se ajusta a la realidad, y por lo tanto es el más valido.

Abstract

In order to make better assessment of intermodal container transportation, the authors have analyzed DEA (Data Envelopment Analysis) method in deciding the most favorable container line from Serbian ports to the near East ports. To allow for applications to a wide variety of activities, term organization unit (Decision Making Unit – DMU) refers to container line. DEA Method has been used to give the estimation of efficiency of operations in organization units. Organization units are container lines in which containers are loaded with mineral water in bottles. The main points in transportation net are factories of mineral water (Knjaz Milos Arandjelovac and Minaqua Novi Sad), Serbian ports ( the Port of Belgrade, the Port of Danube Pancevo and the Port of Prahovo) and nine Mediterranean ports in the near East area. Amount of mineral water that is dispatching from factories to Serbian ports is equal to amount that can be loaded to one container. Having containerized in Serbian ports mineral water is reloaded to the river–sea ships with unified dimensions, so the ships are continuing to travel to the near East ports. The near East ports are the ending points. Input variables in DEA problem are transportation costs and strategy resistance factor in function of container line. Time traveling of one container is in a function of container line and transportation capabilities of container lines are output variables. Transportation costs are counted on the base of integer programming method and Dijkstra algorithm. First Published Online: 05 Oct 2011 Document type: Article