화학공학소재연구정보센터
IEEE Transactions on Automatic Control, Vol.56, No.6, 1235-1246, 2011
Budget Allocation for Effective Data Collection in Predicting an Accurate DEA Efficiency Score
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.