نتایج جستجو برای: imprecise data, ranking

تعداد نتایج: 2436967  

Journal: :international journal of data envelopment analysis 0
a .amirteimoori department of applied mathematics, rasht branch, islamic azad university, rasht, iran. r .farzipoor saen department of industrial management, faculty of management and accounting, islamic azad university – karaj branch, karaj, po box 31485-313, iran. h .azizi department of applied mathematics, parsabad moghan branch, islamic azad university, parsabad moghan, iran.

recently, farzipoor saen [journal of the operational research society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. this short communication aims at showing a computational error in computing the value of preference intensity parameter in farzipoor saen’s [1] ...

Journal: :نظریه تقریب و کاربرد های آن 0
م ایزدیخواه دانشگاه آزاد اراک ز علی اکبر پور دانشگاه آزاد اراک ه شرفی دانشگاه علوم و تحقیقات تهران

envelopment analysis (dea) is a very e ective method to evaluate the relative eciency of decision-making units (dmus). dea models divided all dmus in two categories: ecient and inecientdmus, and don't able to discriminant between ecient dmus. on the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ...

Several methods have been proposed for ranking the decision-making units (DMUs) in data envelopment analysis (DEA) with imprecise data. Some methods have only used the upper bound efficiencies to rank DMUs. However, some other methods have considered both of the lower and upper bound efficiencies to rank DMUs. The current paper shows that these methods did not consider the DEA axioms and may be...

ز علی اکبر پور م ایزدیخواه, ه شرفی

Envelopment Analysis (DEA) is a very eective method to evaluate the relative eciency of decision-making units (DMUs). DEA models divided all DMUs in two categories: ecient and inecientDMUs, and don't able to discriminant between ecient DMUs. On the other hand, the observedvalues of the input and output data in real-life problems are sometimes imprecise or vague, suchas interval data, ordinal da...

Journal: :international journal of data envelopment analysis 2015
hamid sharafi mohsen rostamy-malkhalifeh alireza salehi mohammad izadikhah

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...

2015
D. Anuradha

This paper presents solid assignment problem with imprecise costs. Robust’s ranking method is adopted for ranking the imprecise data. The fuzzy solid assignment problem has been transformed into crisp one and solved by plane point method. Numerical example is provided to illustrate the approach.

Alireza Salehi Hamid Sharafi Mohammad Izadikhah, Mohsen Rostamy-Malkhalifeh,

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...

Journal: :journal of industrial engineering, international 2011
s razavyan g tohidi

this paper introduces discretionary imprecise data in data envelopment analysis (dea) and discusses the efficiency evaluation of decision making units (dmus) with non-discretionary imprecise data. then, suggests a method for evaluation the efficiency of dmus with non-discretionary imprecise data. when some inputs and outputs are imprecise and non-discretionary, the dea model becomes non-linear ...

A .Amirteimoori H .Azizi R .Farzipoor Saen

   Recently, Farzipoor Saen [Journal of the Operational Research Society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. This short communication aims at showing a computational error in computing the value of preference intensity parameter in Farzipoor Saen’s [...

2013
Sébastien Destercke

In this paper, we are interested in the label ranking problem. We are more specifically interested in the recent trend consisting in predicting partial but more accurate (i.e., making less incorrect statements) orders rather than complete ones. To do so, we propose a ranking method based on pairwise imprecise scores obtained from likelihood functions. We discuss how such imprecise scores can be...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید