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Budget Allocation for Effective Data Collection in Predicting an Accurate DEA Efficiency Score

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3 Author(s)
Wai Peng Wong ; Sch. of Manage., Univ. Sains Malaysia, Pulau, Malaysia ; Jaruphongsa, W. ; Loo Hay Lee

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.

Published in:

Automatic Control, IEEE Transactions on  (Volume:56 ,  Issue: 6 )

Date of Publication:

June 2011

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