a strongly interacting dynamic particle swarm optimizational method
A new direct search method using only function values is proposed for finding a local minimizer of a real valued function f(x), x = [x1, x2, ..., xn]T ? Rn. This method is a synthesis of two unconventional trajectory methods for unconstrained minimization. The first is the dynamic method of Snyman [2], and the second method is the particle swarm optimization (PSO) method of Eberhardt and Kennedy [1]. In the new (DYN-PSO) method, the minimization of a function is achieved through the dynamicmotion of a strongly interacting particle swarm, where each particle in the swarm is simultaneously attracted by all other particles located at positions of lower function value.
particle swarm optimization trajectory methods