Abstract
A new model for evolving Evolutionary Algorithms (EAs)
is proposed in this paper. The model is based on the
Multi Expression Programming (MEP) technique. Each MEP
chromosome encodes an evolutionary pattern which is
repeatedly used for generating the individuals of a new
generation. The evolved pattern is embedded into a
standard evolutionary scheme which is used for solving
a particular problem. Several evolutionary algorithms
for function optimisation are evolved by using the
considered model. The evolved evolutionary algorithms
are compared with a human-designed Genetic Algorithm.
Numerical experiments show that the evolved
evolutionary algorithms can compete with standard
approaches for several well-known benchmarking
problems.
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