Behrouz Daneshian
Biographic Data
| ID | 6828672 |
|---|---|
| NAME | Behrouz Daneshian |
| GIVEN NAMES | Behrouz |
| FAMILY NAME | Daneshian |
| SIGNATURE | DANESHIAN B |
| AFFILIATIONS | Islamic Azad University Central Tehran Branch |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Forecast of the efficiency confidence interval of decision-making units in data envelopment analysis
Data Envelopment Analysis (DEA) is a well-known method for calculating the efficiency of Decision-Making Units (DMUs) based on their inputs and outputs. When the data is known and in the form of an interval in a given time period, this method can calculate the efficiency interval. Unfortunately, DEA is not capable of forecasting and estimating the efficiency confidence interval of the units in the future. This article, proposes a efficiency forec…
Ranking of units by corrected cross-efficiency method using optimal weights in the smallest interval
An important method for ranking of decision making units (DMUs) in data envelopment analysis (DEA) is cross-efficiency method. This study proposes a secondary multi-objective model for calculating optimal weights with least dispersion. Firstly, these weights are placed in the smallest interval. Secondly, the cross-efficiency of each of the other units has the least deviation from the CCR efficiency of the same unit. Therefore, optimal weights are…
Modifying the convexity condition in Data Envelopment Analysis (DEA)
Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the…
No prominent works on this page.
Forecast of the efficiency confidence interval of decision-making units in data envelopment analysis
Data Envelopment Analysis (DEA) is a well-known method for calculating the efficiency of Decision-Making Units (DMUs) based on their inputs and outputs. When the data is known and in the form of an interval in a given time period, this method can calculate the efficiency interval. Unfortunately, DEA is not capable of forecasting and estimating the efficiency confidence interval of the units in the future. This article, proposes a efficiency forec…
Ranking of units by corrected cross-efficiency method using optimal weights in the smallest interval
An important method for ranking of decision making units (DMUs) in data envelopment analysis (DEA) is cross-efficiency method. This study proposes a secondary multi-objective model for calculating optimal weights with least dispersion. Firstly, these weights are placed in the smallest interval. Secondly, the cross-efficiency of each of the other units has the least deviation from the CCR efficiency of the same unit. Therefore, optimal weights are…
Modifying the convexity condition in Data Envelopment Analysis (DEA)
Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the…
Computer Science (3 works) · Data envelopment analysis (3 works) · Efficiency Analysis Using DEA (3 works) · Mathematical optimization (3 works) · Mathematics (3 works) · Econometrics (2 works) · Interval (graph theory (2 works) · Set (abstract data type (2 works) · Statistics (2 works) · Artificial Intelligence (1 work)