An Artificial Neural Network Model as the Decision Support System of Ports

Abstract

The new feasibility analysis model proposed in this study for coastal projects consists of three interrelated decision support models: 1) Artificial Neural Network (ANN) to determine the rates and capacity of cargo by considering the economical development of hinterland 2) Queuing model to determine the waiting to service time and the berth occupancy ratios by waiting time modeling of ships using discrete queuing simulation 3) Importance Sampling Monte Carlo (ISMC) to simulate ship arrivals/departures from the quays and to estimate income/expenditure parameters of the coastal project. As a case study, the proposed model was applied to the Iskenderun Pier in Turkey and the future loading/unloading cargo rates of pier were predicted by ANN's. The superiorities of this proposed simulation-ANN model to other classical investment planning methods were the inclusion of uncertainties in the investment parameters like the change of cargo and costs variables in time, and the determination of project benefit/cost with an improved accuracy when compared to classical decision support models.