Data envelopment analysis is a non-parametric linear programming method capable of the efficiency evaluation of decision making units (e.g. public transport companies). It is very often used in the transport sector for the efficiency assessment of airports, ports, railways and public transport companies. However, the original DEA method does not differentiate the efficient firms and thus, does ...

as regards of supper efficiency models which increased thediscrimination power of the standard dea models, still infeasibility mayoccure. in literature there exists some models overcome this difficulty.in this paper a new procedure has been mooted in order to remove thisshortcoming in a way that both input savings and output surplus arebeing considered. this procedure deals with nonradial chang...

Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertai...

on account of the existence of uncertainty, dea occasionally faces the situation of imprecise data, especially when a set of dmus include missing data, ordinal data, interval data, stochastic data, or fuzzy data. therefore, how to evaluate the efficiency of a set of dmus in interval environments is a problem worth studying. in this paper, we discussed the new method for evaluation and ranking i...

because of the piecewise linear nature of the data envelopment analysis (dea) frontier, the optimal multipliers of the dea models may not be unique. choosing weights from alternative optimal solutions of dual multiplier models is one of the most frequently studied subjects in the context of dea. in this paper, the authors have been inspired by the idea of cooper et al. (2011) to propose a linea...

Conventional data envelopment analysis (DEA) assists decision makers in distinguishing between efficient and inefficient decision making units (DMUs) in a homogeneous group. However, DEA does not provide more information about the efficient DMUs. One of the interesting research subjects is to discriminate between efficient DMUs. The aim of this paper is ranking all efficient (extreme and non-ex...

supplier selection is a multi-criteria problem. this study proposes a hybrid model for supporting the suppliers’ selection and ranking. this research is a two-stage model designed to fully rank the suppliers where each supplier has multiple inputs and outputs. first, the supplier evaluation problem is formulated by data envelopment analysis (dea), since the regarded decision deals with uncertai...

data envelopment analysis (dea) is a method used for measuring the efficiency of decision-making units‎. unlike the standard models‎, ‎which assume decision-making units to be a black box‎, ‎network data envelopment analysis focuses on the internal structure of these units‎. ‎some researchers have developed a two-stage method where all the inputs are entirely used in the first stage‎, ‎producin...

efficiency calculations for units belonging to one group according to data envelopment analysis widely have received attention; while experiences related to efficiency comparison of several groups consisted of decision making units is restricted. kao's parallel system network dea model that has been designated aimed at such a comparison, practically leads to accomplish comparison among uni...