A Parallel Strategy for a Genetic Algorithm in Routing Wavelength Assignment Problem Using GPU with CUDA - La-Roque, Esdras; Batista, Cassio; Araújo, Josivaldo (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC), 2020)
This paper presents a parallel strategy with a heuristic approach to reduce the execution time bottleneck of a routing and wavelength assignment problem in wavelength-division multiplexing networks of a previous work that uses a sequential genetic algorithm. As the parallelization solution, the GPU hardware processing on CUDA architecture and CUDA C programming language were adopted. The results achieved were between 35 and 40 times faster than the sequential version of the genetic algorithm.