The optimization calculations are based in genetic algorithms, which takes a pool of the best trials found thus far, mutates (modifies) them, and then crosses them with each other to create a new generation of trials. The best trials from this generation are identified, and this new "elite" group is used to calculate the next generation by mutating them and crossing them with each other. This process is repeated until the improvements over a number of these cycles becomes smaller than a specified convergence tolerance.

Since this process requires many trials to be evaluated, cloud computing is employed to calculate many of these trials in parallel. This decreases the optimization computation time and frees the user's desktop for other processes.