Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2012.2195931
Title: Approximate simulation budget allocation for selecting the best design in the presence of stochastic constraints
Authors: Lee, L.H. 
Pujowidianto, N.A.
Li, L.-W.
Chen, C.-H.
Yap, C.M. 
Keywords: Constrained optimization
optimal computing budget allocation
ranking and selection
simulation
Issue Date: 2012
Source: Lee, L.H., Pujowidianto, N.A., Li, L.-W., Chen, C.-H., Yap, C.M. (2012). Approximate simulation budget allocation for selecting the best design in the presence of stochastic constraints. IEEE Transactions on Automatic Control 57 (11) : 2940-2945. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2012.2195931
Abstract: We develop a new Optimal Computing Budget Allocation (OCBA) approach for the ranking and selection problem with stochastic constraints. The goal is to maximize the probability of correctly selecting the best feasible design within a fixed simulation budget. Based on some approximations, we derive an asymptotic closed-form allocation rule which is easy to compute and implement and can help provide more insights about the allocation. The numerical testing shows that our approach can enhance the simulation efficiency. © 2012 IEEE.
Source Title: IEEE Transactions on Automatic Control
URI: http://scholarbank.nus.edu.sg/handle/10635/63033
ISSN: 00189286
DOI: 10.1109/TAC.2012.2195931
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