The aim of this book is to provide a strong theoretical support for understanding and analyzing
the behavior of evolutionary algorithms as well as for creating a bridge between probability
set-oriented numerics and evolutionary computation. The volume encloses a collection of
contributions that were presented at the EVOLVE 2011 international workshop held in Luxembourg
May 25-27 2011 coming from invited speakers and also from selected regular submissions. The
aim of EVOLVE is to unify the perspectives offered by probability set oriented numerics and
evolutionary computation. EVOLVE focuses on challenging aspects that arise at the passage from
theory to new paradigms and practice elaborating on the foundations of evolutionary algorithms
and theory-inspired methods merged with cutting-edge techniques that ensure performance
guarantee factors. EVOLVE is also intended to foster a growing interest for robust and
efficient methods with a sound theoretical background. The chapters enclose challenging
theoretical findings concrete optimization problems as well as new perspectives. By gathering
contributions from researchers with different backgrounds the book is expected to set the
basis for a unified view and vocabulary where theoretical advancements may echo in different
domains.
