Abstract
We consider the bi-objective simulation optimization (SO) problem on finite sets, that is, an optimization problem where for each system, the two objective functions are estimated as output from a Monte Carlo simulation. The solution to this bi-objective SO problem is a set of non-dominated systems, also called the Pareto set. In this context, we derive the large deviations rate function for the rate of decay of the probability of a misclassification event as a function of the proportion of sample allocated to each competing system. Notably, we account for the presence of dependence between the estimates of each system's performance on the two objectives. The asymptotically optimal allocation maximizes the rate of decay of the probability of misclassification and is the solution to a concave maximization problem.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
