Global optimization inspired by quantum physics

Abstract

Scientists have found that atoms and molecules in nature have an amazing power at finding their global minimal energy states even when their energy landscapes are full of local minima. Recently, the author postulated an optimization algorithm for understanding this fundamental feature of nature. This paper presents a version of this algorithm for attacking continuous optimization problems. On large size benchmark functions, it significantly outperformed the standard particle swarm optimization algorithm. © 2013 Springer-Verlag Berlin Heidelberg.