The Particle Swarm Optimization with Decaying ICMIC for Shortest Path Computation in Computer Networks

In packet-switched computer networks, one of several challenging issues is how to determine an optimal path that satisfies a set of constraints while maintaining high utilization of network resources. This paper proposes an improved particle swarm optimization utilizing Iterative Chaotic Map with Infinite Collapses (ICMIC) perturbations (ICMICPSO) for shortest path computation in computer networks. The chaotic perturbation generated by the ICMIC is incorporated into the particle´s velocity updating rule to make the particles have a larger potential space to fly. With the coefficient of chaotic perturbation decaying, the dynamics of ICMICPSO algorithm is a chaotic dynamics first and then a steepest descent dynamics. The proposed ICMICPSO method as hybrid optimization is tested on several network topologies. Numerical results are compared with that of some other Chaotic PSO methods available in the usual literature. The performance studies demonstrate that the effectiveness and efficiency of the proposed ICMICPSO approach are comparably to or better than that of the other CPSO variants in this paper.