A evolutionary algorithm for solving the single objective static routing and wavelength assignment problem in WDM networks

The static RWA (routing and wavelength assignment) problem in WDM optical network is a combinatorial optimization problem fit to iterative search methods. In this paper we formulate the static RWA problem in optical networks as a single objective optimization problem and solve it in a novel way using a evolutionary algorithm. A hybrid approach based on the k-shortest path for every source-destination pair is used to initialize the population. A special cost function based on the frequency of occurrence of an edge in different source-destination paths is used to evaluate the fitness of a chromosome. A m-point crossover is used to maintain diversity in the solution space. The wavelength assignment to light paths in fittest individuals is performed using a special graph-coloring technique. We compare the single objective results with those obtained by the first-fit algorithm. We tested our algorithm on known optical networks like the ARPANet, EON, UKNet and USFNet. The representative results and the comparison show the effectiveness of our algorithm.