George I. Evers

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—Particle swarm optimization (PSO) is known to suffer from stagnation once particles have prematurely converged to any particular region of the search space. The proposed regrouping PSO (RegPSO) avoids the stagnation problem by automatically triggering swarm regrouping when premature convergence is detected. This mechanism liberates particles from(More)
Particle Swarm Optimization (PSO), which was intended to be a population-based global search method, is known to suffer from premature convergence prior to discovering the true global minimizer. In this thesis, a novel regrouping mechanism is proposed, which aims to liberate particles from the state of premature convergence. This is done by automatically(More)
After deriving the particle swarm equations from basic physics, this paper shows by contradiction that NFL Theorem 1, and consequently Theorems 2 and 3, are irrelevant to continuous optimization. As the discrete nature of matter at its most fundamental level is generally irrelevant from the broader classical perspective, so to is the discrete nature of an(More)
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