A Distributed Implementation of an Improved Particle Swarm Optimization for the Euclidean Steiner Tree Problem in R^N

Euclidean Steiner Tree Problem in Rn consists on finding a minimum length tree of a fixed set of given points in a N-dimensional space (N≥3) with Euclidean metric. This tree spans all these points using, if necessary, extra points (Steiner points). The finding of such solution is a NP-hard problem. This work presents a distributed implementation of a modified metaheuristic based on Improved Particle Swarm Optimization to the problem in question. Finally, computational experiments compare the performance of the proposed distributed heuristic, considering solution’s quality and computational time, over previous works of the literature, proving the effectiveness of the proposed method.