methods of optimization in imprecise data envelopment analysis
Authors
abstract
in this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (idea) and mini-max reference point formulations. through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. in addition, the gradient projection type method can be suggested to determine a normal vector at a given efficient solution on the efficient frontier and to establish an interactive procedure for searching for the most preferred solution (mps) that maximizes the decision maker implicit utility function
similar resources
Methods of Optimization in Imprecise Data Envelopment Analysis
In this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (IDEA) and mini-max reference point formulations. Through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. In addition, the gradient projection type...
full textData envelopment analysis for imprecise data in Buyer-Seller Relationship
In the environment of business‐to‐business e‐commerce, Buyers and sellers in mature industrial markets can turn single transactions into long-term beneficial relationships by a deeper understanding of the complex connection between the two and buyers and sellers are uncertain about their roles. A “must-do” for the sellers, in particular, is to understand patterns of investment and reward,...
full textAn 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 ...
full textA robust optimization approach for imprecise data envelopment analysis
Department of Industrial Engineering, Khajeh Nasir Toosi University, Tehran, Iran b Louvain School of Management, Center of Operations Research and Econometrics (CORE), Universite Catholique de Louvain, 34 Voie du Roman Pays, B-1348 Louvain-le-Neuve, Belgium Management Department, Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA 19141, USA Department of...
full textData envelopment analysis with imprecise data
The conventional data envelopment analysis (DEA) measures the relative efficiencies of a set of decision making units (DMUs) with exact value of inputs and outputs. For imprecise data, i.e., mixtures of interval data and ordinal data, some methods have been developed to calculate the interval of the efficiency scores. This paper constructs a procedure to measure the efficiencies of DMUs with mi...
full textData envelopment scenario analysis with imprecise data
In the existing DEA models, we have a centralized decision maker (DM) who supervises all the operating units. In this paper, we solve a problem in which the centralized DM encounters limited or constant resources for total inputs or total outputs. We establish a DEA target model that solves and deals with such a situation. In our model, we consider the decrease of total input consumption and th...
full textMy Resources
Save resource for easier access later
Journal title:
international journal of data envelopment analysisISSN 2345-458X
volume 1
issue 2 2013
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023