Ordinal Optimization with Computing Budget Allocation for Selecting an Optimal Subset

Mohammad H. Almomani and Mahmoud H. Alrefaei ()
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Mohammad H. Almomani: Faculty of Science, Jerash University, Jerash 26150, Jordan
Mahmoud H. Alrefaei: Department of Mathematics and Statistics, Jordan University of Science and Technology, Irbid 22110, Jordan

Asia-Pacific Journal of Operational Research (APJOR), 2016, vol. 33, issue 02, 1-17

Abstract: In this paper, we consider the problem of selecting the top m systems when the number of alternative systems is very large. We propose a sequential procedure that consists of two stages to solve this problem. The procedure is a combination of the ordinal optimization (OO) technique and optimal computing budget allocation (OCBA) method. In the first stage, the OO is used to select a subset that overlaps with the set of actual best k% systems with high probability. Then in the second stage the optimal computing budget is used to select the top m systems from the selected subset. The proposed procedure is tested on two numerical examples. The numerical tests show that the proposed procedure is able to select a subset of best systems with high probability and short simulation time.

Keywords: Large scale problems; ordinal optimization; optimal computing budget allocation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:33:y:2016:i:02:n:s0217595916500093

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DOI: 10.1142/S0217595916500093

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