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Interactive Algorithm for Obtain the Most Preferred Solution in DEA

M. Moradi Dalini, A.A. Noura


Data envelopment analysis (DEA) evaluates the efficiency of the transformation of a decision making unit’s (DMU’s) inputs to its outputs. One of the important purpose of DEA is to obtain criterions of a DMU. Currently, the criterions are obtained without decision maker’s preferences structure. If the preferences of the decision maker are available, it is very important to obtain the most preferred solution (MPS). By transformed a DEA model into a multiobjective programming (MOP) can be solved them by interactive methods. In interactive methods, a decision maker plays a serious role, such that steps of an algorithm are repeated and the decision maker progressively provides preference information so that MPS can be found. In this regard, we using the interactive PROJECT algorithm to find MPS, based on implicit utility function. This algorithm is able to obtain any efficient solution, contain no supported efficient solution and also identify the MPS, even in nonconvex cases in this study, we will choose one of the DEA models when this model can focus on decreases total input consumption and increase total output production which results in solving one mathematical model instead of n models.


Data envelopment analysis, interactive multi objective programming, implicit utility function, most preferred solution.

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