I have a question regarding one of your gene classes, and I was wondering if I am correct in my approach. I want my GA to evolve the selection of inputs. I want to try and test various combinations of the inputs in evaluating the fitness. I thought that perhaps your FixedBinaryGene class was the best approach, i.e. the allele in a certain position is 1 if the corresponding input is to be included and 0 if not. Also, if I used this approach, then would it be possible to set the length of the gene at run time, in other words, the number of possible inputs to select from? The length wouldn't change once the GA kicks off, however I want to test a few different things, and the number of available inputs for each specific problem is not the same. I noticed in the source code that you referred to JAGA in your implementation. Unfortunately there is not much available on their website, they have pulled down a lot of stuff from their site due to new updates soon to be coming. Nonetheless, I think that this class contains what I need, but I am curious if you can expound a little bit on this class. If you have the time and inclination, can you possibly send me a code snippet that shows how to properly access the bits in a fitness function? I am fairly new to this package, I am still in the process of learning it, I just downloaded it about a month or so ago. I intend to contribute to it once I have something worthwhile to contribute, but I am still under the learning curve. I want to sincerely thank you for all of your time and efforts making this project available for others.