What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Mathematical optimization
Multiple-criteria decision analysis, Management science, Operations research, Artificial intelligence and Evidential reasoning approach are his primary areas of study.
Much of his study explores Multiple-criteria decision analysis relationship to Goal programming.
His research integrates issues of Decision theory, Process and Decision analysis in his study of Management science.
His Operations research research is multidisciplinary, incorporating elements of Data envelopment analysis and Flexibility.
His work carried out in the field of Artificial intelligence brings together such families of science as Linear programming, Machine learning and Decision problem.
The concepts of his Evidential reasoning approach study are interwoven with issues in Decision tree, Optimal decision and Decision model.
His most cited work include:
- Multiple Criteria Decision Analysis: An Integrated Approach (2183 citations)
- Multiple Criteria Decision Analysis (1423 citations)
- A CRITICAL SURVEY ON THE STATUS OF MULTIPLE CRITERIA DECISION MAKING THEORY AND PRACTICE (537 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Multiple-criteria decision analysis, Management science, Operations research, Mathematical optimization and Decision support system.
As a part of the same scientific family, he mostly works in the field of Multiple-criteria decision analysis, focusing on Decision analysis and, on occasion, Optimal decision.
His research in Management science intersects with topics in Data envelopment analysis, Theme, Multicriteria decision and Process.
His work deals with themes such as Purchasing, Project management, Business decision mapping and Decision model, which intersect with Operations research.
His Mathematical optimization research integrates issues from Selection and Land-use planning.
The Decision support system study which covers Decision problem that intersects with Artificial intelligence.
He most often published in these fields:
- Multiple-criteria decision analysis (38.73%)
- Management science (34.51%)
- Operations research (31.69%)
What were the highlights of his more recent work (between 2010-2020)?
- Multiple-criteria decision analysis (38.73%)
- Operations research (31.69%)
- Management science (34.51%)
In recent papers he was focusing on the following fields of study:
Theodor J. Stewart focuses on Multiple-criteria decision analysis, Operations research, Management science, Mathematical optimization and Context.
Theodor J. Stewart performs integrative Multiple-criteria decision analysis and Scenario planning research in his work.
His studies in Operations research integrate themes in fields like Decision support system, Decision problem, Decision analysis and Decision model.
His Decision model research is multidisciplinary, relying on both Decision tree, Optimal decision, Simplicity and Evidential reasoning approach.
His Management science study frequently draws connections to adjacent fields such as Multiple objective.
He has researched Process in several fields, including Range and Agricultural policy.
Between 2010 and 2020, his most popular works were:
- Modeling uncertainty in multi-criteria decision analysis (219 citations)
- Modeling uncertainty in multi-criteria decision analysis (219 citations)
- Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications (196 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Mathematical optimization
Theodor J. Stewart mostly deals with Multiple-criteria decision analysis, Context, Decision analysis, Operations research and Decision model.
Multiple-criteria decision analysis is closely attributed to Management science in his work.
His research investigates the connection with Decision analysis and areas like Optimal decision which intersect with concerns in Evidential reasoning approach, Mathematical optimization and Multi-objective optimization.
His Operations research study combines topics from a wide range of disciplines, such as Econometrics, Decision support system, Artificial intelligence and Decision problem.
His Decision support system study combines topics in areas such as Simplicity, Machine learning, Inference and Heuristics.
His Artificial intelligence study incorporates themes from Linear programming and Goal programming.
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