Genetic routing Algorithm based on adjacency-constraint matrix

MANETs are systematic infrastructureless networks formed of nodes that act as sender, receiver, or router. Node mobility causes frequent topology changes which have negative impact on the network connectivity and performance. Therefore, routing is a serious challenge in such a dynamic environment as reliable paths and most efficient are always required between sources and their destinations. This paper presents routing algorithm based on an adjacency-constraint matrix using Genetic Algorithm (GA). GA presents the feasible paths that encoded in chromosomes that created based on the connectivity matrix. The evaluation function that is based on the adjacency-constraint matrix calculates the fitness values to select the most efficient path. With only two constraints, the performance simulation results of the proposed method showed that it outperforms Dynamic Source Routing (DSR) in term of transmission delay, which is decreased by about 25%.