> That's more difficult. Let's say your variable that contains the required array length is called x. You > either need to decompose your model into two parts (the first part determining x, the second part then > using that solution to construct a new model with the right length), or you need to allocate an array with > the maximum possible length and use constraints to say that everything beyond index x is ignored. > > Cheers, > Guido
Thanks, Guido! I was thinking about an approach similar to your first suggestion which may be better suited for my situation (in addition to being more memory efficient ;-) since it's a natural fit for my solution requirement: I need to solve for every legal length but the data should be randomly picked (one solution for every length) since the data space is very large and most solutions don't add any insight into the problem over that of a single representative solution. I couldn't find an example of model decomposition in MPG, so I'd really appreciate any pointers or hints of handling the underlying space; mainly if I can/must use a different space for the second model. I think I've to use a different space and the variables in the first model can't be constrained by those in the second model in this approach. If there are any such constraints, I must use the second approach of maximum possible length. Thanks, Ajit ==== _______________________________________________ Gecode users mailing list users@gecode.org https://www.gecode.org/mailman/listinfo/gecode-users
