Taxonomy of Low-level Hybridization (LLH) for PSO-GA

Particle Swarm Optimization (PSO) is a popular algorithm used extensively in continuous optimization. One of its well-known drawbacks is its propensity for premature convergence. Many techniques have been proposed for alleviating this problem. One of the popular and promising approaches is low-level hybridization (LLH) of PSO with Genetic Algorithm (GA). Nevertheless, the LLH implementation is considerably difficult due to internal structure modifications of the original hybrid algorithms. Many success works have been reported on LLH for PSO-GA but a wide range of presumption terms and terminology are used. This paper describes the numerous techniques of LLH for PSO-GA in a form of simple taxonomy. Then, examples of several implementation models based on the taxonomy are given. Recent trends are also briefly discussed from an implementations review.