Suresh P. Sethi

Last updated
Suresh P. Sethi
Suresh-sethi-1.JPG
Citizenship United States
Alma mater Carnegie Mellon University
Washington State University
IIT Bombay
Known for Sethi model, Sethi-Skiba point, K-convexity in Rn
Awards Society for Industrial and Applied Mathematics Fellow (2009), IIT Bombay Distinguished Alum (2008)
Scientific career
Fields Operations management, optimal control, Manufacturing, Operations Research, Finance, Economics, Marketing,Industrial Engineering, Optimal Control
Institutions University of Texas at Dallas, University of Toronto, Rice University, Weyerhaeuser Company, Omark Industries, Hindustan Motors, Bhilai Steel Plant
Patrons Eugene McDermott
Thesis Applications of Optimal Control Theory in Management Science and Economics
Doctoral advisor Gerald L. Thompson, Timothy McGuire, Charles Newman,
Other academic advisors George Dantzig
Notable students Subodha Kumar, Steef van de Velde
Website http://www.utdallas.edu/~sethi

Suresh P. Sethi is an American mathematician who is the Eugene McDermott Chair of Operations Management and Director of the Center for Intelligent Supply Networks at the University of Texas at Dallas.

Contents

He has worked as departmental editor of Production and Operations Management , [1] corresponding editor of SIAM Journal on Control and Optimization , and associate editor of Operations Research, Manufacturing & Service Operations Management , and Automatica .

Education

Sethi received his PhD in operations research from Carnegie Mellon University and was a post-doctoral fellow at Stanford University under the supervision of George B. Dantzig. He obtained a B.Tech. with honors in Mechanical Engineering from the Indian Institute of Technology Bombay, an M.S. in Industrial Administration from Carnegie Mellon University, and an Master of Business Administration from Washington State University. [2]

Published books

Research works

Sethi's publications have been cited 31850 times in total, with 86 h-index and 334 i10-index. [3] He has contributed in the fields of manufacturing [4] and operations management, [5] [6] finance [7] and economics, [8] [9] marketing, [10] industrial engineering, [11] [12] operations research, [13] and optimal control. [14] He is known for his developments of the Sethi advertising model and Sethi-Skiba point, and for his textbook on optimal control. [15]

Notable works

Sethi is know for his accomplishments in unifying many theories and concepts in Sethi model, Sethi-Skiba point, K-convexity in Rn Decision and Forecast Horizons, [16] and Supply Chain Coordination with Risk Averse Agents. [17]

Sethi model

The Sethi model describes the process of how sales evolve over time in response to advertising. The model assumes that the rate of change in sales depend on three effects: response to advertising that acts positively on the unsold portion of the market, the loss due to forgetting or possibly due to competitive factors that act negatively on the sold portion of the market, and a random effect that can go either way.[ citation needed ] The following are related journal publications over the years that established and generalized Sethi model.

  1. Naik, P. A.; Prasad, A.; Sethi, S. P. (2008). "[[doi:10.1287/mnsc.1070.0755|Building Brand Awareness in Dynamic *Naik, Prasad A.; Prasad, Ashutosh; Sethi, Suresh P. (January 2008). "Building Brand Awareness in Dynamic Oligopoly Markets". Management Science. 54 (1): 129–138. doi:10.1287/mnsc.1070.0755. ISSN   0025-1909.

Sethi-Skiba point

Sethi-Skiba points arise in optimal control problems that exhibit multiple optimal solutions. A Sethi-Skiba point is an indifference point in an optimal control problem such that starting from such a point, the problem has more than one different optimal solutions.[ citation needed ]

Honors and awards

Sethi has been elected to Production and Operations Management Society (POMS) Fellow in 2005, [18] one of eight individuals up to that time to be honored with that distinction in the field of Operations Management.

He is the recipient of the 2015 Tepper Alumni Achievement Award [19]

Two conferences have been organized in his honor, at Aix-en-Provence in 2005 [20] and at University of Texas at Dallas in 2006. [21] Also, two books have been edited in his honor. [22] [23]

YearHonor/Award
1984-85Connaught Senior Research Fellow, University of Toronto [24]
1996Award of Merit, Canadian Operational Research Society (CORS) [25]
2000Senior Research Fellow, IC2 Institute [26]
2003 IEEE Fellow, [27] INFORMS Fellow, AAAS Fellow [28]
2004 Wickham-Skinner Best Paper Award in Production and Operations Management [29]
2005 Production and Operations Management Society Fellow [30]
2008 IIT Bombay Distinguished Alum [2]
2009 SIAM Fellow, Society for Industrial and Applied Mathematics [31]
2012President, Production and Operations Management Society (POMS) [32]
2015Alumni Achievement Award (Tepper School of Business, Carnegie Mellon University) [33] [19]
2020Sushil K Gupta Production and Operations Management Distinguished Service Award [34]
2024Best Paper Award Named After Suresh Sethi (Production and Operations Management Society) [35]
2021Asia-Pacific Artificial Intelligence Association Fellow [36]
2023 Journal of Operations Management Ambassador Award [37]

Related Research Articles

<span class="mw-page-title-main">Mathematical optimization</span> Study of mathematical algorithms for optimization problems

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In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored. Metaheuristics may make relatively few assumptions about the optimization problem being solved and so may be usable for a variety of problems. Their use is always of interest when exact or other (approximate) methods are not available or are not expedient, either because the calculation time is too long or because, for example, the solution provided is too imprecise.

<span class="mw-page-title-main">Optimal experimental design</span> Experimental design that is optimal with respect to some statistical criterion

In the design of experiments, optimal experimental designs are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith.

Peter Whittle was a mathematician and statistician from New Zealand, working in the fields of stochastic nets, optimal control, time series analysis, stochastic optimisation and stochastic dynamics. From 1967 to 1994, he was the Churchill Professor of Mathematics for Operational Research at the University of Cambridge.

Merton's portfolio problem is a problem in continuous-time finance and in particular intertemporal portfolio choice. An investor must choose how much to consume and must allocate their wealth between stocks and a risk-free asset so as to maximize expected utility. The problem was formulated and solved by Robert C. Merton in 1969 both for finite lifetimes and for the infinite case. Research has continued to extend and generalize the model to include factors like transaction costs and bankruptcy.

Stochastic optimization (SO) are optimization methods that generate and use random variables. For stochastic optimization problems, the objective functions or constraints are random. Stochastic optimization also include methods with random iterates. Some hybrid methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization. Stochastic optimization methods generalize deterministic methods for deterministic problems.

The value function of an optimization problem gives the value attained by the objective function at a solution, while only depending on the parameters of the problem. In a controlled dynamical system, the value function represents the optimal payoff of the system over the interval [t, t1] when started at the time-t state variable x(t)=x. If the objective function represents some cost that is to be minimized, the value function can be interpreted as the cost to finish the optimal program, and is thus referred to as "cost-to-go function." In an economic context, where the objective function usually represents utility, the value function is conceptually equivalent to the indirect utility function.

Stochastic control or stochastic optimal control is a sub field of control theory that deals with the existence of uncertainty either in observations or in the noise that drives the evolution of the system. The system designer assumes, in a Bayesian probability-driven fashion, that random noise with known probability distribution affects the evolution and observation of the state variables. Stochastic control aims to design the time path of the controlled variables that performs the desired control task with minimum cost, somehow defined, despite the presence of this noise. The context may be either discrete time or continuous time.

<span class="mw-page-title-main">Yu-Chi Ho</span> American control theorist

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Material theory is the sub-specialty within operations research and operations management that is concerned with the design of production/inventory systems to minimize costs: it studies the decisions faced by firms and the military in connection with manufacturing, warehousing, supply chains, spare part allocation and so on and provides the mathematical foundation for logistics. The inventory control problem is the problem faced by a firm that must decide how much to order in each time period to meet demand for its products. The problem can be modeled using mathematical techniques of optimal control, dynamic programming and network optimization. The study of such models is part of inventory theory.

Sethi-Skiba points, also known as DNSS points, arise in optimal control problems that exhibit multiple optimal solutions. A Sethi-Skiba point is an indifference point in an optimal control problem such that starting from such a point, the problem has more than one different optimal solutions. A good discussion of such points can be found in Grass et al.

The Sethi model was developed by Suresh P. Sethi and describes the process of how sales evolve over time in response to advertising. The model assumes that the rate of change in sales depend on three effects: response to advertising that acts positively on the unsold portion of the market, the loss due to forgetting or possibly due to competitive factors that act negatively on the sold portion of the market, and a random effect that can go either way.

Anatoly Aleksandrovich Zhigljavsky is a professor of Statistics in the School of Mathematics at Cardiff University. He has authored 12 monographs and over 150 papers in refereed journals. His research interests include stochastic and high-dimensional global optimisation, time series analysis, multivariate data analysis, statistical modeling in market research, probabilistic methods in search and number theory.

In economics, non-convexity refers to violations of the convexity assumptions of elementary economics. Basic economics textbooks concentrate on consumers with convex preferences and convex budget sets and on producers with convex production sets; for convex models, the predicted economic behavior is well understood. When convexity assumptions are violated, then many of the good properties of competitive markets need not hold: Thus, non-convexity is associated with market failures, where supply and demand differ or where market equilibria can be inefficient. Non-convex economies are studied with nonsmooth analysis, which is a generalization of convex analysis.

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Vivek Shripad Borkar is an Indian electrical engineer, mathematician and an Institute chair professor at the Indian Institute of Technology, Mumbai. He is known for introducing analytical paradigm in stochastic optimal control processes and is an elected fellow of all the three major Indian science academies viz. the Indian Academy of Sciences, Indian National Science Academy and the National Academy of Sciences, India. He also holds elected fellowships of The World Academy of Sciences, Institute of Electrical and Electronics Engineers, Indian National Academy of Engineering and the American Mathematical Society. The Council of Scientific and Industrial Research, the apex agency of the Government of India for scientific research, awarded him the Shanti Swarup Bhatnagar Prize for Science and Technology, one of the highest Indian science awards for his contributions to Engineering Sciences in 1992. He received the TWAS Prize of the World Academy of Sciences in 2009.

In mathematics, unscented optimal control combines the notion of the unscented transform with deterministic optimal control to address a class of uncertain optimal control problems. It is a specific application of tychastic optimal control theory, which is a generalization of Riemmann-Stieltjes optimal control theory, a concept introduced by Ross and his coworkers.

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K-convexity in Rn is a mathematical concept.

References

  1. https://journals.sagepub.com/editorial-board/pao [ bare URL ]
  2. 1 2 "Dr. Suresh Pal Sethi". Indian Institute of Technology Bombay. Retrieved 2024-08-01.
  3. "Suresh Sethi". scholar.google.com. Retrieved 2024-08-21.
  4. Sethi, Suresh P.; Zhang, Qing (1994). Hierarchical Decision Making in Stochastic Manufacturing Systems. doi:10.1007/978-1-4612-0285-1. ISBN   978-1-4612-6694-5.
  5. Haruvy, Ernan; Sethi, Suresh P.; Zhou, Jing (2008). "Open Source Development with a Commercial Complementary Product or Service". Production and Operations Management. 17 (1): 29–43. doi:10.3401/poms.1070.0004. ISSN   1059-1478.
  6. Markovian Demand Inventory Models. International Series in Operations Research & Management Science. Vol. 108. 2010. doi:10.1007/978-0-387-71604-6. ISBN   978-0-387-56563-7.
  7. Sethi, Suresh P. (1997). Optimal Consumption and Investment with Bankruptcy. doi:10.1007/978-1-4615-6257-3. ISBN   978-1-4613-7871-6.
  8. Arrow, Kenneth J.; Bensoussan, Alain; Feng, Qi; Sethi, Suresh P. (2007). "Optimal savings and the value of population". Proceedings of the National Academy of Sciences. 104 (47): 18421–18426. Bibcode:2007PNAS..10418421A. doi: 10.1073/pnas.0708030104 . PMC   2141792 . PMID   17984059.
  9. Boucekkine, Raouf; Hritonenko, Natali; Yatsenko, Yuri, eds. (2013). Optimal Control of Age-structured Populations in Economy, Demography, and the Environment. doi:10.4324/9780203844557. ISBN   9781136920936.
  10. Sethi, Suresh P. (1983). "Deterministic and stochastic optimization of a dynamic advertising model". Optimal Control Applications and Methods. 4 (2): 179–184. doi:10.1002/oca.4660040207. S2CID   123673289.
  11. Throughput Optimization in Robotic Cells. International Series in Operations Research & Management Science. Vol. 101. 2007. doi:10.1007/0-387-70988-6. ISBN   978-0-387-70987-1. S2CID   60059332.
  12. Sethi, Suresh P.; Bogataj, Marija; Ros-Mcdonnell, Lorenzo, eds. (2012). Industrial Engineering: Innovative Networks. doi:10.1007/978-1-4471-2321-7. ISBN   978-1-4471-2320-0.
  13. Bes, C.; Sethi, S. P. (1988). "Concepts of Forecast and Decision Horizons: Applications to Dynamic Stochastic Optimization Problems". Mathematics of Operations Research. 13 (2): 295–310. doi:10.1287/moor.13.2.295. S2CID   5840100.
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  15. Sethi, S.P. and Thompson, G.L., Optimal Control Theory: Applications to Management Science and Economics, Second Edition, Springer, 2000. ISBN   0-387-28092-8 and ISBN   0-7923-8608-6.
  16. Rempala, Ryszarda; Sethi, Suresh (July 1992). "Decision and forecast horizons for one-dimensional optimal control problems: Existence results and applications". Optimal Control Applications and Methods. 13 (3): 179–192. doi:10.1002/oca.4660130302. ISSN   0143-2087.
  17. Gan, Xianghua; Sethi, Suresh P.; Yan, Houmin (June 2004). "Coordination of Supply Chains with Risk-Averse Agents". Production and Operations Management. 13 (2): 135–149. doi:10.1111/j.1937-5956.2004.tb00150.x. ISSN   1059-1478.
  18. "UTD's Dr. Suresh Sethi Is Elected POMS Fellow". News Center. Retrieved 2024-09-04.
  19. 1 2 TepperCMU (2016-04-12). Suresh Sethi, Ph.D '72 | Recipient of the 2015 Tepper Alumni Achievement Award . Retrieved 2024-07-31 via YouTube.
  20. Optimal Control and Dynamic Games: Workshop in Honor of Suresh Sethi, Aix en Provence, France, June 2–6, 2005.
  21. International Conference on Management Sciences: Optimization Models and Applications in Honor of Professor Suresh Sethi, University of Texas at Dallas, Richardson, TX, May 20–22, 2006.
  22. M1 Stochastic Processes, Optimization, and Control Theory: Applications in Financial Engineering, Queueing Networks, and Manufacturing Systems: A Volume in Honor of Suresh Sethi; Series: International Series in Operations Research & Management Science, Vol. 94, H. Yan, G. Yin, and Q. Zhang (Eds.), Springer, 2006. (360 pages – ISBN   978-0-387-33770-8)
  23. Optimal Control and Dynamic Games, Applications in Finance, Management Science and Economics, Series: Advances in Computational Management Science, Vol. 7, C. Deissenberg and R.F. Hartl (Eds.), Springer, Netherlands, 2005. (344 pages – ISBN   978-0-387-25804-1)
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