Abstract:
Intelligent analysis and designing of network routing provides an edge in this
increasingly fast era. In this work, a variation of Genetic Algorithm (GA) for finding the
Optimized shortest path of the network is presented. The algorithm finds the optimal path
by using an objective function consisting of the bandwidth and delay metrics of the
network and also through bandwidth and utilization metrics. The main distinguishing
element of this work is the use 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. Therefore, the best chromosomes are crossed
over and give the most suitable offsprings. If the resulting offsprings are least fitted, they
are discarded. Mutation operation is used for maintaining the population diversity.
Various experiments have been performed 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 that proposed
algorithm finds the optimal shortest path more efficiently than existing algorithms.
