Optimization of multimodal transportation routes based on traveling salesman problems and integration into intelligent transportation systems

The globalizing world and the growing economy cause the companies have to find new quests to survive in the economic competitive environment. The fact that Raw materials and production costs are at almost the same level in the same sectors foreground the logistics. Because Logistics plays an active role at every stage from the supply of raw materials to the suplly of products to customers. An optimization that can be done at logistics will directly affect the corporate and enterprise economies. In this study, an multimodal transport optimization experiment was carried out with particle swarm optimization (PSO) based on the traveling salesman problem (TSP). Logistic villages and commercial ports were selected which are suitable for transportation mode change for multimodal transport. With optimization, we have solved three parameters for distance, time and cost for Unimodal Road Transport and Multimodal Transportation which are widely used in our country. The solutions for each parameter were compared and evaluated separately for Unimodal Road Transport and Multimodal Transport. Multimodal transport is seen to be more advantageous for three separate parameters as a result of evaluation. Finally, The integration of the optimization into intelligent transport systems (ITS) has been investigated.