Mitchell, T. J. (2010) An exploration of evolutionary computation ...

in chapter three. Diversity within the crowding model is maintained by adopting an
overlapping (generational) strategy in which offspring replace their progenitors based not
on fitness, but similarity in the genotype space.
In the next section of this thesis, the state-of-the-art ES is briefly examined, providing the
general framework on which the algorithms presented throughout chapters four and five of
this thesis are based.
2.3.2 Evolution Strategies
While EP was being developed in the U.S.A., two engineers at the Technical University of
Berlin were independently developing their own evolution-inspired parameter optimisation
technique known as the evolutionsstrategie. The earliest ES, developed by Rechenberg
(1965), implemented a set of simple rules for the sequential design and analysis of real-
world parametric engineering problems.
The ES models the processes of evolution at the phenotypic level. As such, search points
are represented directly as n-dimensional vectors of (usually) real-valued object variables
. As well as representing object variables, individuals (denoted ) also include a set
of endogenous strategy parameters , as well as a fitness value, equal to its objective
function result :
The original two-membered ES (the so-called ES) employs a simple
mutation/selection mechanism, in which a single parent is mutated to produce a single
offspring. If the mutation is found to be profitable the offspring replaces its parent,
otherwise, the offspring is discarded. Later, multi-membered ESs were developed in which
populations of parent and offspring individuals are maintained by the algorithm. The two
most notable of these population-based ESs were introduced by Schwefel (1981) and
constitute:
the strategy, in which
parents are varied to produce offspring, and
parents of the subsequent generation are selected from all individuals.
the strategy, in which selection is made among only the
are systematically discarded regardless of their fitness value.
The pseudocode for the basic multi-membered ES is provided in figure 2.3.
offspring. Parents
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