Network coding optimization based on the genetic algorithm with memory function

Network coding technology brought benefits for us, but also brought us the corresponding expenses. Kim et al. put forward the network coding optimization to reduce cost. In this paper, the problem of network coding optimization is improved, at first we use graph decomposition method constructing the network coding optimization model, then we propose the genetic algorithm with memory function (MGA, Genetic Algorithm with Memory). This paper got the MGA using the orthogonal crossover operator, trust and neighborhood for the simple genetic algorithm. The result of simulation experiment shows that the speed of - MGA getting the solution from network coding optimization model is much faster and the quality of the solution is better (that is to say the average number of the coding node is less in the network coding scheme).