This class implements the IPOP (increased population size) restart strategy ES, which increases
the ES population size (i.e., lambda) after phases of stagnation and then restarts the optimization
by reinitializing the individuals and operators.
Stagnation is for this implementation defined by a FitnessConvergenceTerminator instance
which terminates if the absolute change in fitness is below a threshold (default 10e-12) for a
certain number of generations (default: 10+floor(30*n/lambda) for problem dimension n).
If the MutateESRankMuCMA mutation operator is employed, additional criteria are used for restarts, such as numeric conditions of the covariance matrix. Lambda is increased multiplicatively for every restart, and typical initial values are mu=5, lambda=10, incFact=2. The IPOP-CMA-ES won the CEC 2005 benchmark challenge. Refer to Auger&Hansen 05 for more details.