An improved electromagnetism-like algorithm for constrained optimization problems

Abstract

Electromagnetism-like algorithm (EMA) is a population based meta-heuristic algorithm, which simulates the attraction-repulsion mechanism between charged particles in an electrical field. In this study, modifications to traditional EMA are proposed to solve constrained optimization problems. A modified electrical charge calculation, a probabilistic particle selection mechanism and a re-generation step are adapted to the algorithm. The improved algorithm is tested on 13 benchmark problems and compared to novel meta-heuristics. The computational results reveal that the proposed algorithm is very efficient.