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

purpose function optimiser by Fogel (1992). Simultaneously, Rechenberg (1965) was
working independently on an adaptive optimiser known as the evolution strategy (ES).
Contemporary evolution-inspired function optimisers are descended from one of these
three interpretations, which have, since their introduction, been applied to an ever-
increasing number of engineering problems. For a diverse list of applications the reader is
directed to Schwefel and Bäck (1997), Bäck et al (1997a) and Rothlauf et al (2005).
Although these three classes of EA are not without difference, each models the processes
of evolution to some degree. At an abstract level, evolution can be regarded as the
mechanism by which sophisticated and well adapted biological structures have come to
exist: a process of natural selection which emerges when there is a superfluity of genetic
material within an environment in which individuals struggle for existence.
Just as a breeder chooses those individuals closest to his desired optimum, and
discards the rest, so the natural environment improves the performance of a species
by eliminating the less effective. Individuals possessing particular adaptations will
survive better, and by virtue of the heritable nature of these adaptations, they will
transmit them to their offspring. Gradually, the adaptations will spread and
improve so that the species will become better suited to the environment which it
inhabits.
2.2 The Evolutionary Algorithm
When the principles of evolution are simulated and used to optimise solutions to
Parkin (1979)
engineering problems, the individuals, referred to in the above quote, are represented by a
population of potential solutions. The environment, which is defined by a given objective
function, quantifies the relative worth or fitness of each solution. Adaptations are
introduced by recombining and mutating individuals from one generation to produce the
offspring that form the next. The elimination of less effective genetic material is facilitated
by selecting those individuals with above average fitness to partake in reproduction more
frequently than those with below average fitness. This selective bias introduces the notion
of natural selection, enabling well adapted genes to propagate throughout subsequent
generations. A simple representation of this evolutionary model is provided in figure 2.1.
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