A fuzzy-particle swarm optimization based algorithm for solving shortest path problem

In this paper, an efficient particle swarm optimization (PSO) algorithm based on fuzzy logic for solving the single source shortest path problem (SPP) is proposed. A particle encoding/decoding scheme has been devised for particle-representation of the SPP parameters, which is free of the previously randomized path construction methods in computational problems like the SPP .The search capability of PSO is diversified by hybridizing the PSO with fuzzy logic. The local optimums will not be the point of convergence for the particles and the global optimum will be found in a shorter period of time if the PSO is correctly modified using fuzzy logic rules. Numerical computation results on several networks with random weights illustrate the efficiency of the proposed method for computation of the shortest paths in networks.