Route Selection Problem Based on Hopfield Neural Network

Transport network is a key factor of economic, social and every other form of development in the region and the state itself. One of the main conditions for transport network development is the construction of new routes. Often, the construction of regional roads is dominant, since the design and construction in urban areas is quite limited. The process of analysis and planning the new roads is a complex process that depends on many factors (the physical characteristics of the terrain, the economic situation, political decisions, environmental impact, etc.) and can take several months. These factors directly or indirectly affect the final solution, and in combination with project limitations and requirements, sometimes can be mutually opposed. In this paper, we present one software solution that aims to find Pareto optimal path for preliminary design of the new roadway. The proposed algorithm is based on many different factors (physical and social) with the ability of their increase. This solution is implemented using Hopfield's neural network, as a kind of artificial intelligence, which has shown very good results for solving complex optimization problems