Optimal tolerance allotment using a genetic algorithm and truncated Monte Carlo simulation

As is typical of stochastic-optimization problems, the multivariate integration of the probability-density function is the most difficult task in the optimal allotment of tolerances. In this paper, a truncated Monte Carlo simulation and a genetic algorithm are used as analysis (i.e. multivariate-integration) and synthesis (i.e. optimization) tools, respectively. The new method has performed robustly in limited experiments, and was able to provide a significant reduction in optimal cost when compared with results published in a previous study.