ESTIMATION OF PASSENGER-KILOMETER AND TONNE-KILOMETER VALUES FOR HIGHWAY TRANSPORTATION IN TURKEY USING THE FLOWER POLLINATION ALGORITHM

Within the scope of this study, intercity passenger and freight movements in Turkey are estimated by using the flower pollination algorithm (FPA), while demand forecasts are performed on transport systems considering possible future scenarios. Since the passenger and freight transport system in Turkey mainly involves road transport, passenger-kilometer and tonne-kilometer values of this system are estimated. By relying on three independent parameters, models were developed in three different forms: linear, force and semi-quadratic. Population (P) between 1990 and 2016, gross domestic product per capita (GDPperC) in US dollars and the number of vehicles were used as input parameters for the development of the models. When the passenger-kilometer models were created, the number of cars, buses and minibuses that are predominantly used for passenger transportation was preferred for the number of vehicles, while the number of trucks and vans used for cargo transportation were taken into consideration in the tonne-kilometer models. The coefficients of the models were determined by FPA optimization, with models developed to estimate passenger-kilometer and tonne-kilometer values. The model results were compared with the observation values and their performance was evaluated. Two different scenarios were created to estimate passenger-kilometer and tonne-kilometer in 2030. Parallel to the increase in population and welfare level, it is predicted that demand for passenger and freight transport will increase. In particular, the higher input parameter values in Scenario 1 significantly affect the increase in demand, leading to a demand increase of around 50%. In addition, the FPA has demonstrated effective performance in predicting the demand for passenger and freight transport and that it can be used in many different areas.