I have never found an efficient use of GA for training a fixed topology NN. The only successful adaptive topology NNs I have designed had a single hidden layer with a variable number of elliptical or radial basis functions. However, they were not designed using GA.
I have posted a fixed topology tansig GA design recently
However, the design was more illustrative than useful.
My point of view is that GAs probably excel when the net topology is more complex than the MATLAB feedforward and feedback defaults. In particular, when both number of layers, nodes and connections are variable.
If there is an efficient way to combine GA and backprop I am not familiar with it. (Which doesn't necessarily mean that it doesn't exist).
Good Luck.
PS If you find a good reference, PLEASE let us know.
Thanks in advance,
Greg
