An effective approach to smartly allocate computing budget for discrete event simulation

Ordinal Optimization concentrates on isolating a subset of good designs with high probability and reduces the required simulation time dramatically for discrete event simulation. To obtain the same probability level, we may smartly allocate our computing budget among different designs, instead of equally simulating all designs. In this paper we present an effective approach to smartly allocate computing budget for DES simulation. While Ordinal Optimization can dramatically reduce computation cost, our approach can further reduce the already-low cost. Numerical testing shows an additional factor of ten speed-up