Application of the artificial immune system to determine the priorities for the development of the transportation network

A transportation network provides the transport requirements of moving people and goods with different destination goals and relocation directions. The current network structure is usually a result of historically long adaptation process and the probability that now it is not optimal is very high. Additionally, nowadays it can be observed a strong growth of transportation needs. This paper deals with the problem of the transportation network development in response to the increasing demands. The task is to minimize the total network impedance taking into account the constrains of the investment budget. A bi-level model of the transportation network consisting of some classes of road links was developed. At the upper level the objective function-reduction of total travel time for all vehicles, at the lower level optimal distribution of traffic is searched for. The main aim was to indicate the most advantageous directions of development of the transportation network without exceeding the budget. In the paper was shown that the problem can be quickly solved by the application of the Artificial Immune System. Artificial Immune Systems are inspired by biological mechanisms defending the living organisms against pathogens. Generally, they are very powerful tool, because they can adapt and learn. Apart from many other applications it is possible to use an Artificial Immune System for optimization. Additionally the comparison with the simulated annealing algorithm was here performed.