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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.