“Genetic algorithms essentially mimic evolutionary biology to find optimal solutions. Initially, they select a population of solutions based on some evaluation criteria, then use some subset of that population—the fittest members—as breeding stock for the subsequent generation of solutions. This process continues for multiple generations, each getting closer to an optimal solution. This article describes my experience with parallel design and discusses how to make parallel design more collaborative.” (Mike Myles – UXmatters)