Finding feasible systems in the presence of constraints on multiple performance measures

We consider the problem of finding a set of feasible or near-feasible systems among a finite number of simulated systems in the presence of constraints on secondary performance measures. We first present a generic procedure that detects the feasibility of one system in the presence of one constraint and extend it to the case of two or more systems and constraints. To accelerate the elimination of infeasible systems, a method that reuses collected observations and its variance-updating version are discussed. Experimental results are presented to compare the performance of the proposed procedures.