I’m sort of torn on what to do for implementation of my distributed genetic algorithm problem. I would like to be able to have nodes join and part at will and not take down the whole system. But this introduces the problem of mismatch of generations. Often times a genetic algorithm simulation is capped by a certain amount of generations and if I have a node that is on 75 out of 100 generations and a brand new node joins the cluster I’m not sure if I should fake it and start at 75 and copy one of the other nodes as a starting point or have it start out at 0 and potentially have the results delayed until the end of execution of the new node. I was hoping someone had some input on what they could see as problems in addition to a long wait time with this new node if I start at 0, I am struggling to think of what could go wrong in both approaches other than that.