Data envelopment analysis (DEA) is an important way of data mining. In this paper we show that the inverse data envelopment analysis (IDEA) model can be used to estimate inputs for a decision making unit (DMU): if among a group of decision making units, we increase certain outputs to a particular unit and assume that the DMU maintains its current efficiency level with respect to other units, how much more inputs should be provided to the unit? The problem is transformed into a multi-objective programming problem to solve. We use one example to illustrate our computation method and through the example we can also see the difference between the method presented in paper [8] and our method proposed here.
Citation:
Yu-quan Cui, Li-jie Ma, Jianmin Wang, "A New Method of Estimating Inputs," isda, vol. 1, pp.718-723, Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) Volume 1, 2006