 Recently, Khodabakhshi and Aryavash have introduced a ranking method [Applied Mathematics Letters, 25 (2012) 2066-2070.], which is based on an optimistic-pessimistic approach of data envelopment analysis (DEA). This method ranks all decision making units according to a combination of their minimum and maximum possible efficiency scores which are determined by solving two linear programming mo...

Some of the parameters in issues of the reality world are uncertainty. One of the uncertain problems with the qualitative parameters is economic problems such as bankruptcy problem. In this case, there is a probability of dealing with imprecise concepts including the intervals regarding the official’s viewpoint, organizations’ managers. Accordingly, this article uses the concepts of data envelo...

data envelopment analysis (dea) is a method to measure relative efficiency of a set of decision-making units (dmus) which uses multiple inputs and produces multiple outputs. in the conventional dea, crisp inputs and outputs are fundamentally necessary. but the observed values of inputs and outputs in real-world problems are sometimes imprecise. thus, performance measurement often needs to be do...

We propose a new approach to testing conformance to a nondeterministic specification , in which testing proceeds only as long as increased test coverage is guaranteed. In testing that a system meets a nondeterministic specification [1], it is usually assumed that the system is fair to each transition of the specification (i.e., the system will make every possible nondeterministic choice if give...

Data envelopment analysis (DEA) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. It is based on solving linear programming problems. Since 1978 when basic DEA model was introduced many its modifications were formulated. Among them are two or multi-stage models with serial or parallel structure often called net...