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Title: Optimal computing budget allocation for constrained optimization
Keywords: Constrained optimization, multiple performance measures, simulation, ranking & selection, optimal computing budget allocation, closed-form expressions
Issue Date: 3-Aug-2012
Citation: NUGROHO ARTADI PUJOWIDIANTO (2012-08-03). Optimal computing budget allocation for constrained optimization. ScholarBank@NUS Repository.
Abstract: We consider the constrained optimization problem from a finite set of designs where their main objective and the constraint measures must be estimated via stochastic simulation. As simulation is time-consuming, two procedures are proposed to maximize the probability of correct selection given a fixed computing budget. First, an approximate allocation procedure is derived based on Bonferroni bounds which are applicable for the cases with independent and correlated performance measures. Secondly, an asymptotically optimal allocation procedure is derived using large deviations theory which is able to explicitly account for the impact of the correlation among the multiple performance measures. As the number of the designs becomes large, the optimal allocation can be approximated by closed-form expressions which are simple and easy-to-implement. The numerical results show that the proposed procedures can enhance the simulation efficiency. An application example of the proposed procedure to a hospital bed allocation problem is also provided.
Appears in Collections:Ph.D Theses (Open)

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