Krzysztof Pawlas; Davood Zall MCS-2012-21, pp. 90. COM/School of Computing, 2012.
Objectives. In this study we review previous attempts in forecasting country seaborne container throughput, analyze them and then classify in form of table to provide a concrete base for researchers in this field.
Another aim of this study is to provide a Decision Support System (DSS) to assist experts in port management and forecast their country seaborne container demand. It will lead to reasonable decisions so as to provide sufficient supply which handles containers demand. This DSS, is a global forecasting model which can be applied to every country, independently of their specific parameters.
Methods. In theoretical phase a number of scientific databases such as: Google Scholar, ACM, SCOPUS, IEEE, SpringerLink and some other are used to collect previous studies. After review and analysis, selected papers are classified in a form of table to provide a complete resource for us as well as future researchers in this field.
In order to provide appropriate model, we combine System Dynamics modeling with Genetic Programming to provide an accurate and reliable model. This model is the result of the analysis of previous studies and applied in this study for the first time.
Results. Our final model was applied to two cases (Sweden and China) and provides provided reliable results for both countries. To analyze the uncertain variables in the model, Monte Carlo simulation was used to assess the sensitivity of our model. In order to compare with other methods, we conducted a case study with Artificial Neural Network (ANN) and compared the results of our model and ANN. The results show the disadvantages of statistical methods to system dynamics. Additionally to compare with other attempts, our model was confronted with another study which provided a model for Finland. By comparing and considering their advantages and disadvantages we found out that our simplified model could be applied as a global model to other countries.
Conclusions. We conclude that our model is an appropriate DSS to assist experts, forecast their country throughput and make appropriate decisions so as to invest, extending their ports in right time. The application of Genetic Programming in our model provides accurate mathematical equations for the influencing variables which even may not need to calibrate the model. It is a global model which can be applied to different countries but still requires more experiments to prove this claim.