Comparison of Genetic Algorithm and Simulated Annealing Technique for Optimal Path Selection In Network Routing

This paper addresses the path selection problem from a known sender to the receiver. The proposed work shows path selection using genetic algorithm(GA)and simulated annealing (SA) approaches. In genetic algorithm approach, the multi point crossover and mutation helps in determining the optimal path and also alternate path if required. The input to both the algorithms is a learnt module which is a part of the cognitive router that takes care of four QoS parameters.The aim of the approach is to maximize the bandwidth along the forward channels and minimize the route length. The population size is considered as the N nodes participating in the network scenario, which will be limited to a known size of topology. The simulated results show that, by using genetic algorithm approach, the probability of shortest path convergence is higher as the number of iteration goes up whereas in simulated annealing the number of iterations had no influence to attain better results as it acts on random principle of selection.