  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.
