Study On Optimizations For Route Selection And Capacity And Flow Assignment In Networks Based On Improved Particle Swarm Algorithm

Route selection of the messages and capacity and flow assignment (CFA) of every link are two important factors on performance optimization in computer communication networks. It is of great importance to solve the problems reasonably for improving the network's real time performance, increasing the utilization of the network resource, lowering its construction cost and soon. But the two problems are complex nonlinear programming which has many restrained conditions and it is known to be NP-completeness in combinatorial optimization. The results generated by traditional optimization methods can not satisfy all requirements of engineering. The particle swarm optimization algorithm based on swarm intelligence is improved in the paper. And the improved PSO algorithm is applied in the route selection and CFA problems for the first time. The inertia weight factor is improved to linearly attenuating varying weight in the improved algorithm, and the linearly varying studying factor, the simulated annealing mechanism, the mutation operation and neighboring search strategy are added to raising performance in the algorithm. A great number of experimental results simulated by computer show that, the near overall optimal solution by using the improved PSO algorithm can be solved, and the quality of solution can be greatly improved in comparison with the traditional Lagrangean relaxation algorithm. And comparing with tabu search algorithm, genetic algorithm, improved genetic algorithm, simulated annealing algorithm, the method in the paper also show advantages more or less.The investigation results in this paper are of important theoretical value and have broad application prospects, not only for the computer communication networks, but also for the networks in telecommunication, electric power and transportation fields. And it is good for broadening the application of PSO algorithm.