Self-Organizing Migrating Algorithm with non-binary perturbation

Abstract

The self-organizing migrating algorithm (SOMA) is a popular population base metaheuristic. One of its key mechanisms is a perturbation of the individual movement with a binary-valued perturbation (PRT) vector. The goal of perturbation is to improve the diversity of the population and exploration of the search space. In this paper, we study a variant of the SOMA algorithm with non-binary PRT vector. We investigate the effect of introducing a third possible value, a negative (repulsive) element, into the PRT vector. The aim is to slow the population convergence and prolong the exploration phase. The inspiration is taken from previous successful implementations of repulsive mechanics in another swarm-based method: the Particle Swarm Optimization. © Springer Nature Switzerland AG 2020.