What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical optimization
- Random variable
His scientific interests lie mostly in Queueing theory, Mathematical optimization, Industrial engineering, Stochastic ordering and Discrete mathematics.
J. George Shanthikumar has researched Queueing theory in several fields, including Service, Job shop, Expected value, Queue and Server.
His studies deal with areas such as Entropic value at risk, Expected shortfall, Dynamic risk measure and Nonlinear programming as well as Mathematical optimization.
J. George Shanthikumar interconnects Manufacturing engineering, Operations management and Fair-share scheduling in the investigation of issues within Industrial engineering.
His biological study spans a wide range of topics, including Multiplicity and Multivariate random variable.
He combines subjects such as Telecommunication network reliability, Reliability, Random variable and Convexity with his study of Discrete mathematics.
His most cited work include:
- Stochastic orders and their applications (1913 citations)
- Stochastic models of manufacturing systems (1329 citations)
- Convex separable optimization is not much harder than linear optimization (199 citations)
What are the main themes of his work throughout his whole career to date?
J. George Shanthikumar focuses on Mathematical optimization, Queueing theory, Queue, Stochastic ordering and Discrete mathematics.
His Mathematical optimization research is multidisciplinary, relying on both Scheduling and Regret.
His study looks at the relationship between Queueing theory and topics such as Stochastic process, which overlap with Markov process.
His work in Queue covers topics such as Service which are related to areas like Operations management.
His work carried out in the field of Stochastic ordering brings together such families of science as Reliability theory, Multivariate statistics and Combinatorics.
His Discrete mathematics research incorporates themes from Random variable and Convexity.
He most often published in these fields:
- Mathematical optimization (29.20%)
- Queueing theory (16.81%)
- Queue (15.04%)
What were the highlights of his more recent work (between 2012-2021)?
- Mathematical optimization (29.20%)
- Operations management (6.19%)
- Supply chain (3.98%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Operations management, Supply chain, Production and Supply chain management.
The study incorporates disciplines such as Profit and Resource allocation in addition to Mathematical optimization.
The various areas that J. George Shanthikumar examines in his Supply chain study include Systems design, Mathematical economics, Strategic planning and Function.
J. George Shanthikumar interconnects Profit and Nonlinear system in the investigation of issues within Mathematical economics.
His work in Production addresses issues such as Variety, which are connected to fields such as Mass customization and Simple.
His research in Convex optimization focuses on subjects like Theory of computation, which are connected to Stochastic ordering.
Between 2012 and 2021, his most popular works were:
- How Research in Production and Operations Management May Evolve in the Era of Big Data (47 citations)
- The patient assignment problem in home health care: using a data-driven method to estimate the travel times of care givers (34 citations)
- Incentive for Peer‐to‐Peer Knowledge Sharing among Farmers in Developing Economies (22 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical optimization
- Mathematical analysis
His primary areas of investigation include Mathematical optimization, Operations management, Supply chain management, Econometrics and Big data.
His Mathematical optimization study incorporates themes from Stockout and Markov model.
His Operations management research is multidisciplinary, incorporating elements of Production and Estimation.
His Supply chain management research incorporates elements of Supply and demand, Quantile regression, Personalization and Operations research.
His Econometrics study integrates concerns from other disciplines, such as Reliability theory, Statistics, Multivariate statistics and Hazard.
His Big data research includes elements of Function, Supply chain, Service system, Data analysis and Process management.
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.
