In this note, we extend an evolutionary stochastic portfolio optimization
framework to include probabilistic constraints. Both the stochastic
programming-based modeling environment as well as the evolutionary optimization
environment are ideally suited for an integration of various types of
probabilistic constraints. We show an approach on how to integrate these
constraints. Numerical results using recent financial data substantiate the
applicability of the presented approach