The underlying invention generally relates to the field of Estimation of
Distribution Algorithm, especially to optimization problems, including
single-objective optimization and Multi-Objective Optimization.The
proposed method for optimization comprises six steps. In a first step it
provides an initial population or a data set with a plurality of members
respectively represented by parameter sets. Then one or a plurality of
fitness functions are applied to evaluate the quality of the members of
the population. In a third step offspring of the population is generated
by means of a stochastic model using information from all members of the
population. One or a plurality of fitness functions are applied to
evaluate the quality of the offspring with respect to the underlying
problem of the optimization. In a fifth step offspring is selected.
Lastly the method goes back to the third step until the quality reaches a
threshold value.