Particle swarm optimization with noising metaheuristics for solving network shortest path problem

This paper presents an efficient particle swarm optimization (PSO) based search algorithm for solving the single source shortest path problem (SPP), commonly encountered in graph theory. A particle encoding/decoding scheme has been devised for particle-representation of the SPP parameters. The search capability of PSO is diversified by hybridizing the PSO with a noising metaheuristics. Numerical computation results on several networks with random topologies illustrate the efficiency of the proposed hybrid PSO-noising method for computation of shortest paths in networks.