Please use this identifier to cite or link to this item: https://doi.org/10.1109/TASE.2013.2239289
Title: Optimal computing budget allocation for complete ranking
Authors: Xiao, H.
Lee, L.H. 
Ng, K.M. 
Keywords: Complete ranking
heuristic algorithm
large deviation theory
optimal computing budget allocation
simulation
Issue Date: 2014
Source: Xiao, H., Lee, L.H., Ng, K.M. (2014). Optimal computing budget allocation for complete ranking. IEEE Transactions on Automation Science and Engineering 11 (2) : 516-524. ScholarBank@NUS Repository. https://doi.org/10.1109/TASE.2013.2239289
Abstract: Previous research in ranking and selection focused on selecting the best design and subset selection. Little research has been done for ranking all designs completely. Complete ranking has been applied to design of experiment, random number generator and population-based search algorithms. In this paper, we consider the problem of ranking all designs. Our objective is to develop an efficient simulation allocation procedure that maximizes the probability of correct ranking with fixed limited computing budget. A previous allocation strategy of complete ranking based on indifference zone formulation is conservative and not efficient enough. We use the optimal computing budget allocation framework to further enhance the efficiency and reduce the amount of budget needed to achieve the same probability of correct ranking. Compared with the previous allocation strategy, our proposed allocation rule performs best under different scenarios. © 2013 IEEE.
Source Title: IEEE Transactions on Automation Science and Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/87134
ISSN: 15455955
DOI: 10.1109/TASE.2013.2239289
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