Issues on the optimisation of evolutionary algorithms code
Proceedings of the 2002 Congress on Evolutionary Computation. CEC …, 2002•ieeexplore.ieee.org
The aim of this paper is to show that the common belief, in the evolutionary community, that
evaluation time usually takes over 90% of the total time, is far from being always true. In fact,
many real-world applications showed a much lower percentage. This raises several
questions, one of them being the balance between fitness and operators computational
complexity: what is the use of elaborating smart evolutionary operators to reduce the number
of evaluations if as a result, the total computation time is increased?.
evaluation time usually takes over 90% of the total time, is far from being always true. In fact,
many real-world applications showed a much lower percentage. This raises several
questions, one of them being the balance between fitness and operators computational
complexity: what is the use of elaborating smart evolutionary operators to reduce the number
of evaluations if as a result, the total computation time is increased?.
The aim of this paper is to show that the common belief, in the evolutionary community, that evaluation time usually takes over 90% of the total time, is far from being always true. In fact, many real-world applications showed a much lower percentage. This raises several questions, one of them being the balance between fitness and operators computational complexity: what is the use of elaborating smart evolutionary operators to reduce the number of evaluations if as a result, the total computation time is increased?.
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