Application of Evolutionary Algorithms to Global Cluster Geometry Optimization

Abstract

This contribution focuses upon the application of evolutionary algorithms to the nondeterministic polynomial hard problem of global cluster geometry optimization. The first years of method development in this area are sketched briefly; followed by a characterization of the current state of the art by an overview of recent application work. Strengths and weaknesses of this approach are highlighted by comparison with alternative methods. Last but not least, current method development trends and desirable future development directions are summarized.