Particle Swarm Optimization for Multi-constrained Routing in Telecommunication Networks

By our analysis, the QoS routing is the optimization problem under the satisfaction of multiple QoS constraints. The Particles Swarm Optimization (PSO) is an optimization algorithm which has been applied to finding shortest path in the network. However, it might fall into local optimal solution, and is not able to solve the routing based on multiple constraints. To tackle this problem, we propose a new method of solving the multiple constraints routing. This paper firstly sets up a multi constrained QoS routing model and constructs the fitness value function by transforming the QoS constraints with a penalty function. Secondly, the iterative formulas of the original PSO are improved to tailor to non-continuous search space of the routing problem. Finally, the natural selection and mutation ideas of the Genetic Algorithm (GA) are applied to the PSO to improve the convergent performance. The simulation results show that the proposed GA-PSO algorithm can not only successfully solve the multi-constrained QoS routing problem, but also achieves a better effect in the success rate of the searching optimal path.