Routing optimization strategy using Genetic Algorithm utilizing bandwidth and delay

Intelligent analysis and designing of network routing provides an edge in this increasingly fast era. In this work, we present a variation of Genetic Algorithm (GA) for finding the Optimized shortest path of the network. The algorithm finds the optimal path by using an objective function consisting of the bandwidth and delay metrics of the network. We also introduce the concept of ¿2-point over 1-point crossover¿. The population comprises of all chromosomes (feasible and infeasible). Moreover, it is of variable length, so that the algorithm can perform efficiently in all scenarios. Rank-based selection is used for cross-over operation. Mutation operation is used for maintaining the population diversity. We have also performed various experiments for the population selection. The experiments indicate that random selection method is the most optimum. Hence, the population is selected randomly once the generation is developed. The results prove our assertion that our proposed algorithm finds the optimal shortest path more efficiently than existing algorithms. In this work, we have shown the results using a smaller network; however the work for larger network is in progress.