The Urban Path Routing Adjustable Optimization by Means of Wavelet Transform and Multistage Genetic Algorithm

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. Wavelet transform as the first part of proposed algorithm derives edges risk. Finally, multistage genetic algorithm operates to find the optimal solution which is defined as the shortest path. The proposed algorithm is applied to the case study. The performances of the algorithm is investigated by comparing with other methods.