The expected opportunity cost and selecting the optimal subset

In this paper, we discuss the concept of the expected opportunity cost of a potentially incorrect selection as a measure of selection quality on a new selection procedure that is used to selecting the top m systems for large scale problems. This procedure is used the ordinal optimiza- tion method to reduce the size of the search space, and then it is used the idea of computing budget allocation OCBA-m to identify the top m systems from the survivors systems that we got it by ordinal opti- mization method. This procedure is tested on two numerical examples, buffer allocation problem BAP and M/M/1 queuing system. Clearly from the numerical results this procedure selects the optimal subset of systems with the minimum expected opportunity cost of a potentially incorrect selection.