  The Java implementation of a portfolio of parameter-less evolutionary
algorithms is presented. The Parameter-less Evolutionary Portfolio implements a
heuristic that performs adaptive selection of parameter-less evolutionary
algorithms in accordance with performance criteria that are measured during
running time. At present time, the portfolio includes three parameter-less
evolutionary algorithms: Parameter-less Univariate Marginal Distribution
Algorithm, Parameter-less Extended Compact Genetic Algorithm, and
Parameter-less Hierarchical Bayesian Optimization Algorithm. Initial
experiments showed that the parameter-less portfolio can solve various classes
of problems without the need for any prior parameter setting technique and with
an increase in computational effort that can be considered acceptable.
