‎in this paper, we present a two-stage model for ranking of decision making units (dmus) using interval analytic hierarchy process (ahp). since the efficiency score of unity is assigned to the efficient units, we evaluate the efficiency of each dmu by basic dea models and calculate the weights of the criteria using proposed model. in the first stage, the proposed model evaluates decision making...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...

data envelope analysis (dea) is an approach to estimate the relative efficiency of decision making units (dmus). several studies were conducted in order to prioritize efficient units and some useful models such as cross-efficiency matrix (cem) were presented.  besides, a number of dea models with interval data have been developed and ranking dmus with such data was solved. however, presenting a...

This research aims at presenting a consolidated model of data envelopment analysis (DEA) technique and value engineering to select the best manufacturing methods for gate valve covers and ranking the methods using TOPSIS.To do so, efficiency evaluation indices were selected based on the value engineering approach and different manufacturing methods were evaluated using DEA technique.Finally, ef...

According to the growing trend of IT-based systems, implementation of computerized maintenance management system (CMMS) in Iran’s power industry can dramatically help in optimized management of maintenance activities, and thereby, reducing equipment failures, increasing reliability, increasing product stability and, above all, increasing efficiency and productivity of the employees of this indu...

The purpose of this paper is to evaluate the revenue efficiency in the fuzzy network data envelopment analysis‎. ‎Precision measurements in real-world data are not practically possible‎, ‎so assuming that data is crisp in solving problems is not a valid assumption‎. ‎One way to deal with imprecise data is fuzzy data‎. ‎In this paper‎, ‎linear ranking functions are used to transform the full fuz...

In this paper, a method is proposed to calculate a comprehensive index that calculates the ecological efficiency of a city by combining together the measurements provided by some Data Envelopment Analysis (DEA) cross-efficiency models using the Shannon’s entropy index. The DEA models include non-discretionary uncontrollable inputs, desirable and undesirable outputs. The method is implemented to...

Learning to Rank (LtR) is the machine learning method of choice for producing highly effective ranking functions. However, efficiency and effectiveness are two competing forces and trading off effectiveness for meeting efficiency constraints typical of production systems is one of the most urgent issues. This extended abstract shortly summarizes the work in [4] proposing CLEaVER, a new framewor...

Data envelopment analysis (DEA) calculates the relative efficiency of homogenous decision-making units (DMUs) with multiple inputs and outputs. Classic DEA models usually suffer from several issues such as: discrimination power, variable weights of inputs/outputs, inaccurate efficiency estimation for small number of DMUs, incapability in working with zero and negative data, and not having exter...

A growing number of highly optimized reasoning algorithms have been developed to allow inference tasks on expressive ontology languages such as OWL(DL). Nevertheless, there is broad agreement that a reasoner could be optimized for some, but not all the ontologies. This particular fact makes it hard to select the best performing reasoner to handle a given ontology, especially for novice users. I...