Patent ID: 8793200
Filing Date: 2014-07-29
Classification: G06N

Abstract:
1. A system implementing particle swami optimization, the system comprising one or more processors that are configured to perform operations of: operating a plurality of software agents as a cooperative swarm to locate an optimum of an objective function, wherein each agent is assigned an initial velocity vector to explore a multi-dimensional solution space, where each agent is configured to perform at least one iteration, the iteration being a search in the multi-dimensional solution space for the optimum of the objective function, where each agent keeps track of a first position vector representing a current best solution y wherein in a first phase, the plurality of software agents randomly explore the multi-dimensional solution space utilizing a random walk process to locate, the optimum of the objective function; wherein in a second phase that follows the first phase, the velocity and position vectors for a particle i are updated probabilistically to locate the optimum of the objective function; wherein in the first phase, each agent is driven by a random force according to the following: wherein for t≧1, y i and y g and are computed according to: where {right arrow over (x i )}(t) is a position vector and {right arrow over (v i )}(t) is a velocity vector at an iteration t of an i-th agent, w is a momentum constant that prevents premature convergence of the agents, x is a constriction factor which influences the convergence of the agents, c 0 is a constant, q 0 (t) is a vector with the same dimension as {right arrow over (v i )} or {right arrow over (x i )} with a set of uniformly distributed random components in [−1.0, 1.0] drawn on each iteration, wherein the current best y i and the global best y g computed in the first phase are used as an initial current best y i and global best y g in the second phase; wherein the first phase runs for a predetermined number of iterations prior to initiation of the second phase; and wherein the plurality of software agents converge at a position in the multi-dimensional solution space representing an optimum of the objective function, wherein the objective function is J({right arrow over (y)}