An algorithm for Data Envelopment Analysis (DEA).1
نویسنده
چکیده
Data envelopment analysis is computationally intensive. The standard approach requires the solution of as many LPs as there are points in the data domain, each with as many columns. This number is frequently in the thousands and multi-period DEA amplifies the problem. Enhancements that reduce the size of the LPs are possible and a new scheme consisting of partitioning the domain offers more time savings for certain problems. The new DEA procedure we present is fundamentally different from anything proposed to date. It is based on an algorithm to identify directly the extreme elements of the DEA production possibility set. These extreme elements are then used in a second phase to find the DEA score for the rest of the data adding flexibility to the analysis. The procedure we introduce applies to any of the four “convexified” free-disposability DEA models. Extensive computational testing verifies and validates the new procedure and demonstrates that it is computationally superior to what is currently available.
منابع مشابه
A new approach based on data envelopment analysis with double frontiers for ranking the discovered rules from data mining
Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...
متن کاملUsing Non-Archimedean DEA Models for Classification of DMUs: A New Algorithm
A new algorithm for classification of DMUs to efficient and inefficient units in data envelopment analysis is presented. This algorithm uses the non-Archimedean Charnes-Cooper-Rhodes[1] (CCR) model. Also, it applies an assurance value for the non-Archimedean using only simple computations on inputs and outputs of DMUs (see [18]). The convergence and efficiency of the ne...
متن کاملAn algorithm for the anchor points of the PPS of the CCR model
Anchor DMUs are a new class in the general classification of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). An anchor DMU in DEA is an extreme-efficient DMU that defines the transition from the efficient frontier to the free-disposability part of the boundary of the Production Possibility Set (PPS). In this paper, the anchor points of the PPS of the CCR model are investigated....
متن کاملAn algorithm for determining common weights by concept of membership function
Data envelopment analysis (DEA) is a method to evaluate the relative efficiency of decision making units (DMUs). In this method, the issue has always been to determine a set of weights for each DMU which often caused many problems. Since the DEA models also have the multi-objective linear programming (MOLP) problems nature, a rational relationship can be established between MOLP and DEA problem...
متن کاملAn improved approach to find and rank BCC-efficient DMUs in data envelopment analysis (DEA)
Recently, a mixed integer data envelopment analysis (DEA) model has been proposed to find the most BCC-efficient (or the best) decision making unit (DMU) by Toloo (2012). This paper shows that the model may be infeasible in some cases, and when the model is feasible, it may fail to identify the most efficient DMU, correctly. We develop an improved model to find the most BCC-efficient DMU that r...
متن کاملDesigning a new multi-objective fuzzy stochastic DEA model in a dynamic environment to estimate efficiency of decision making units (Case Study: An Iranian Petroleum Company)
This paper presents a new multi-objective fuzzy stochastic data envelopment analysis model (MOFS-DEA) under mean chance constraints and common weights to estimate the efficiency of decision making units for future financial periods of them. In the initial MOFS-DEA model, the outputs and inputs are characterized by random triangular fuzzy variables with normal distribution, in which ...
متن کامل