文件名称:FuzzyPSO_2010-(1)
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A Fuzzy-Particle Swarm Optimization Based Algorithm for Solving Shortest Path
Problem.
Abstract—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
Problem.
Abstract—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
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