Fecha de publicación: 29/07/2014 Fuente: WIPO "swarm" Described is a method for particle swarm optimization (PSO) utilizing a random walk process. A plurality of software agents is configured to operate as a cooperative swarm to locate an optimum of an objective function. The method described herein comprises two phases. In a first phase, the plurality of software agents randomly explores the multi-dimensional solution space by undergoing a Brownian motion style random walk process. In a second phase, the velocity and position vectors for each particle are updated probabilistically according to a PSO algorithm. By allowing the particles to undergo a random walk phase, the particles have an increased opportunity to explore their neighborhood, land in the neighborhood of a true optimum, and avoid prematurely converging on a sub-optimum. The present invention improves on what is currently known by increasing the success rate of the PSO algorithm in addition to reducing the required computation.