Routing optimization for electric cargo commercial vehicles

The world has now started to rapidly switch to renewable energy. Now, the use of oil in the world is gradually decreasing and studies for a cleaner and healthier ecosystem are progressing rapidly. In this context, the development of electric vehicles has come a long way. Electric vehicles have begun to find a place in transportation, which has a great place in the consumer society. Commercial vehicles, which take up the most space in transportation, cause environmental pollution day by day and harm living things. Thus, the consumption of fossil fuels has increased. In this thesis, our aim is to prevent this and to create an advantage in most aspects by minimizing consumption and as short as possible with electric commercial vehicles. With this thesis, it is aimed that today's cargo companies will go to their destination as soon as possible by reducing the cost with renewable energy and saving time. In this thesis, the most suitable route will be calculated by taking into account the range that the vehicle can travel according to its state of charge, and it will be ensured that it goes to the destination at the optimum time and/or with energy consumption. The routes to be calculated will be displayed to the users on the map in the mobile environment, and it will be ensured that they reach their destination with the most suitable route. For example, on the Elazig province map, for the purpose of optimization according to the determined scenarios, how much energy consumption will be when the delivery is made to the target addresses by an electric commercial vehicle in the shortest time has been calculated. Calculations were made through simulations to be made in the computer environment. Methods such as Capacity Constrained Vehicle Routing Problem (KKARP), Time Constrained Vehicle Routing Problem (ZKARP), Electric Vehicle Routing Problems (EARP) were used. In addition, mapping systems on the internet such as Google Maps have been used. When the routings are completed according to the vehicle's charge, the target location will be shared for use in mobile applications..