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|Title:||Budget allocation for effective data collection in predicting an accurate DEA efficiency score|
optimal computing budget allocation algorithms (OCBA)
stochastic data envelopment analysis (DEA)
|Citation:||Wong, W.P., Jaruphongsa, W., Lee, L.H. (2011-06). Budget allocation for effective data collection in predicting an accurate DEA efficiency score. IEEE Transactions on Automatic Control 56 (6) : 1235-1246. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2010.2088870|
|Abstract:||We analyze how to allocate the budget for data collection effectively when data envelopment analysis (DEA) is used for predicting the efficiency. We formulate this problem under a Bayesian framework and propose two heuristics algorithms, i.e., a gradient-based algorithm and a hybrid GA algorithm to solve this optimization problem. Our results indicate that effective allocation of budget for data collection can greatly reduce the overall data collection effort in comparison with a uniform budget allocation. © 2006 IEEE.|
|Source Title:||IEEE Transactions on Automatic Control|
|Appears in Collections:||Staff Publications|
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