The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

Supplier evaluation and selection are critical decision making processes that require consideration of a variety of attributes. Several studies have been performed for effective evaluation and selection of suppliers by utilizing several techniques such as linear weighting methods, mathematical programming models, statistical methods and AI based techniques. One of the successful evaluation meth...

Data envelopment analysis (DEA) is a mathematical programming method in Operations Research that can be used to distinguish between efficient and inefficient decision making units (DMUs). However, the conventional DEA models do not have the ability to rank the efficient DMUs. This article suggests bootstrapping method for ranking measures of technical efficiency as calculated via non-radial mod...

In this paper we present a method for measuring the efficiency for any economical branch. We construct the econometric approach of production frontiers, using the DEA technique (Data envelopment analysis), based on the mathematical programming approach. We effectuate an analysis of some certain data concerning the efficiency or the inefficiency of the branches, using the Efficiency Measurement ...

This paper presents a novel approach to achieving the goals of data envelopment analysis in the process of reconstruction and integration of decision-making units by using multiple objective linear programming. In this regard, first, we review inverse data envelopment analysis models for data reconstruction and integration. We present a model with multi-objective linear programming structure in...

For better guiding a system, senior managers should have accurate information. Using Data Envelopment analysis (DEA) help managers in this objective. Thus, many investigations have been made in order to find the most productive scale size (MPSS) for the evaluating decision making units (DMUs). In this paper we consider this case where there exist subsets of input and output variables to be inte...

Data envelopment analysis (DEA) is a mathematical programming technique for identifying efficiency scores of decision making units (DMUs). Since DEA models cannot present efficient frontiers of PPS, in order to do this, we introduce a method for identifying efficient frontier for DMUs with interval data.

Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. This paper shows the method of Discriminant Analysis (DA), on Imprecise Data by Data Envelopment 724 F. Hosseinzadeh Lotfi et al Analysis (DEA). DEA-Discriminant Analysis (DEA-DA) is designed to identify the existence or n...

Container terminal production is both an important and complicated element in the contemporary global economy. Amongst other methods, the efficiency of container port or terminal production can potentially be analysed by Data Envelopment Analysis (DEA) or by the Free Disposal Hull (FDH) Model. This paper aims to evaluate the efficiency of the world’s most important container ports and terminals...

In the today’s world wherein every routine is based on economic factors, there is no doubt that theoretical sciences are driven by their capabilities and affordances in terms of economy. As a mathematical tool, data envelopment analysis (DEA) is provided to economics, so that one can investigate associated costs, prices and revenues of economic units. Data Envelopment Analysis (DEA) is a linear...