Using Enhanced Russell Model to Solve Inverse Data Envelopment Analysis Problems
نویسندگان
چکیده
منابع مشابه
Using Enhanced Russell Model to Solve Inverse Data Envelopment Analysis Problems
This paper studies the inverse data envelopment analysis using the nonradial enhanced Russell model. Necessary and sufficient conditions for inputs/outputs determination are introduced based on Pareto solutions of multiple-objective linear programming. In addition, an approach is investigated to identify extra input/lack output in each of input/output components (maximum/minimum reduction/incre...
متن کاملInverse DEA Using Enhanced Russell Measure in the Presence of Fuzzy Data
The present study deals with the inverse DEA using the non-radial Enhanced Russell (ER)-measure in the presence of fuzzy data. This paper proposes a technique to treat the fuzzy data in the problem of simultaneous estimation of input-output levels. Necessary and sufficient conditions are provided for ER-measure maintaining in the presence of fuzzy data. A numerical example with real data is pre...
متن کاملGeneralized Fuzzy Inverse Data envelopment Analysis Models
Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...
متن کاملLearning to solve inverse problems using Wasserstein loss
We propose using the Wasserstein loss for training in inverse problems. In particular, we consider a learned primal-dual reconstruction scheme for ill-posed inverse problems using the Wasserstein distance as loss function in the learning. This is motivated by miss-alignments in training data, which when using standard mean squared error loss could severely degrade reconstruction quality. We pro...
متن کاملAn Extension to Imprecise Data Envelopment Analysis
The standard data envelopment analysis (DEA) method assumes that the values for inputs and outputs are exact. While DEA assumes exact data, the existing imprecise DEA (IDEA) assumes that the values for some inputs and outputs are only known to lie within bounded intervals, and other data are known only up to an order. In many real applications of DEA, there are cases in which some of the input ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Scientific World Journal
سال: 2014
ISSN: 2356-6140,1537-744X
DOI: 10.1155/2014/571896