What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical optimization
- Artificial intelligence
His primary areas of study are Data envelopment analysis, Mathematical optimization, Ranking, Data mining and Operations research.
His Data envelopment analysis study incorporates themes from Inefficiency, Computational complexity theory, Decision support system, Linear programming and Numerical analysis.
Gholam Reza Jahanshahloo studied Mathematical optimization and Fuzzy number that intersect with Fuzzy classification.
His Ranking research incorporates elements of TOPSIS, Interval and Extension.
Gholam Reza Jahanshahloo works mostly in the field of Data mining, limiting it down to topics relating to Cross efficiency and, in certain cases, Selection and Matrix, as a part of the same area of interest.
His studies deal with areas such as Preference, Type-2 fuzzy sets and systems and Preference theory as well as Multiple-criteria decision analysis.
His most cited work include:
- Extension of the TOPSIS method for decision-making problems with fuzzy data (425 citations)
- An algorithmic method to extend TOPSIS for decision-making problems with interval data (416 citations)
- Efficiency Analysis and Ranking of DMUs with Fuzzy Data (168 citations)
What are the main themes of his work throughout his whole career to date?
Data envelopment analysis, Mathematical optimization, Econometrics, Linear programming and Ranking are his primary areas of study.
His Data envelopment analysis research is multidisciplinary, incorporating elements of Returns to scale, Numerical analysis, Data mining and Operations research.
His Mathematical optimization research is multidisciplinary, relying on both Function, Production, Interval and Fuzzy logic.
His Interval research is multidisciplinary, incorporating perspectives in TOPSIS, Upper and lower bounds and Algorithm.
Gholam Reza Jahanshahloo has researched Linear programming in several fields, including Additive model and Multiple objective.
His Cross efficiency study, which is part of a larger body of work in Ranking, is frequently linked to Rank, bridging the gap between disciplines.
He most often published in these fields:
- Data envelopment analysis (72.64%)
- Mathematical optimization (53.73%)
- Econometrics (21.89%)
What were the highlights of his more recent work (between 2012-2021)?
- Data envelopment analysis (72.64%)
- Mathematical optimization (53.73%)
- Econometrics (21.89%)
In recent papers he was focusing on the following fields of study:
Gholam Reza Jahanshahloo mostly deals with Data envelopment analysis, Mathematical optimization, Econometrics, Linear programming and Ranking.
His research integrates issues of Data mining, Inefficiency, Reduction, Benchmark and Operations research in his study of Data envelopment analysis.
His biological study spans a wide range of topics, including Production and Structure.
His Econometrics research incorporates themes from Elasticity, Statistics and Operations management.
His Linear programming research focuses on subjects like Hyperplane, which are linked to Computation, Additive model and Measure.
His research in Ranking intersects with topics in Matrix, Selection and Rank.
Between 2012 and 2021, his most popular works were:
- A Review of Ranking Models in Data Envelopment Analysis (67 citations)
- Inverse DEA under inter-temporal dependence using multiple-objective programming (34 citations)
- Recognizing strong and weak congestion slack based in data envelopment analysis (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical optimization
- Artificial intelligence
Gholam Reza Jahanshahloo focuses on Data envelopment analysis, Mathematical optimization, Ranking, Data mining and Rank.
His studies in Data envelopment analysis integrate themes in fields like Production, Inefficiency, Econometrics, Measure and Operations research.
His Measure study combines topics in areas such as Negative integer and Feature.
The study of Mathematical optimization is intertwined with the study of Simple in a number of ways.
His Ranking research includes elements of Matrix, Selection and Rank.
His Data mining research integrates issues from Computational intelligence, Super efficiency and Representation theorem.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
