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Evolving evolutionary algorithms with patterns
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DOI：10.1007/s00500-006-0079-1.png)
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Abstract
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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 optimization 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.
Keywords:
genetic algorithms
genetic programming
evolving evolutionary algorithms
multi expression programming
linear genetic programming
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