Inproceedings,
A Highly Efficient Function Optimization with Genetic Programming
Late Breaking Papers at the 2004 Genetic and Evolutionary Computation Conference, Seattle, Washington, USA, (26 July 2004)
Abstract
This paper describes a new approach for function
optimisation that uses a novel representation for the
parameters to be optimised. By using genetic
programming using, the new method evolves functions
that transform initial random values for the parameters
into optimal ones. Moreover, the new approach addresses
the scalability problem by using a representation that,
in principle, is independent of the size of the problem
being addressed. Promising results are reported,
comparing the new method with differential evolution
and particle swarm optimisation on a test suite of
benchmark problems.
