Predicting the trim of vessels to achieve optimal fuel consumption by mathematical modelling (case study of container vessels)

One of the main concerns and challenges in the marine transportation industry is the energy consumption of vessels, efforts to reduce fuel consumption in addition to money saving decreases emission of greenhouse gases and atmospheric pollutants. The purpose of this research is to provide a model that reduces the fuel consumption of vessels to a considerable extent and beside saving money and reducing dependence on imported fuels, the volume of greenhouse gases can be determined. In order to achieve this goal, mixed research method utilized, first the main parameters which affecting fuel consumption are extracted from the literature, then optimal model is obtained by using mathematical modelling and artificial neural network prediction algorithms. In this research, 4years daily information of 6 vessels with 2000 TEU (container) was utilized as research dataset for mathematical modelling. Then the intelligent decision support system was developed based on main parameters, which includes two artificial neural network models for fuel consumption performance prediction and vessel trim optimization. This system fulfils its evaluation tests, with acceptable validity and reliability values. Based on the designed intelligent decision-making model, it was determined by using test data that, designed system reduces fuel consumption by optimizing trim parameter to %4.41 on average.