Please use this identifier to cite or link to this item: https://doi.org/10.1109/9.739080
Title: Explanation of goal softening in ordinal optimization
Authors: Lee, L.H. 
Lau, T.W.E.
Ho, Y.C.
Keywords: Alignment probability
Order statistics
Selection algorithms
Stochastic optimization
Issue Date: 1999
Source: Lee, L.H.,Lau, T.W.E.,Ho, Y.C. (1999). Explanation of goal softening in ordinal optimization. IEEE Transactions on Automatic Control 44 (1) : 94-99. ScholarBank@NUS Repository. https://doi.org/10.1109/9.739080
Abstract: The authors explain the role of goal softening in the convergence of alignment probability employed in Ordinal Optimization. Using the an order statistics formulation, they examine the exponential decrease of misalignment probability bounds when two or more designs are compared. Their conclusion states that, by relaxing the good enough subset and selected subset criteria, it is exponentially efficient in terms of matching good designs in a selected group.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/63125
ISSN: 00189286
DOI: 10.1109/9.739080
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