A Comparative Analysis for Determining the Optimal Path using PSO and GA
This is an incremental improvement for network routing optimization, comparing existing methods.
The paper tackled the problem of finding optimal paths in network routing by comparing particle swarm optimization (PSO) and genetic algorithm (GA), finding that PSO converged faster than GA.
Significant research has been carried out recently to find the optimal path in network routing. Among them, the evolutionary algorithm approach is an area where work is carried out extensively. We in this paper have used particle swarm optimization (PSO) and genetic algorithm (GA) for finding the optimal path and the concept of region based network is introduced along with the use of indirect encoding. We demonstrate the advantage of fitness value and hop count in both PSO and GA. A comparative study of PSO and genetic algorithm (GA) is carried out, and it was found that PSO converged to arrive at the optimal path much faster than GA.