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

• Published in: 2007 IEEE International Conference on Telecommunications and Malaysia International Conference on Communications pp. 354 - 359
• Main Authors: Mohemmed, A.W., Sahoo, N.C., Tan Kim Geok
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2007
• Subjects: Birds; Computer networks; Costs; Decoding; Graph theory; Joining processes; Marine animals; Particle swarm optimization; Sequences; Shortest path problem
• ISBN: 9781424410934; 1424410932
• DOI: 10.1109/ICTMICC.2007.4448659

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.