Intelligent optimization approach for the k shortest paths problem based on genetic algorithm

To address the k shortest paths (KSP) problem, an intelligent optimization approach based on Genetic Algorithm (GA) is presented in this paper. A simple and intuitive natural path representation is firstly employed to be the chromosome encoding scheme. Then genetic operators specific to this encoding scheme are defined respectively. Each partial route of two chosen chromosomes is exchanged by a one-point crossover operator at common intersections. A one and two-point mutation operators are adopted to perform mutation operations for directed and undirected graphs respectively. And a bidirectional searching strategy is applied to eliminate loops in the paths generated by the above genetic operators. Comparative experiments were conducted on test graphs by using different strategies of genetic operations, mutation rates and operators. And the experimental results verify the validity of the proposed algorithm.