Jayant Rajgopal


My research interests are focused primarily on operations research and its applications. Although I am always open to working on interesting research problems that combine the use of quantitative/analytical techniques with computers, my current focus is on two broad (and interconnected) areas:

Supply Chain Analysis

Applications of IE/OR to Healthcare Delivery

In the past, I have also worked on more focused topics including 

Geometric Programming 

Systems Reliability

My preference is for things that are continuous (i.e., just let me differentiate it ...) and deterministic (uncertainty is annoying...).  But at the end of the day, it's more important for the problem to (1) be interesting and (2) be real.

Supply Chain Analysis

I have worked for many years in the general area of supply chains, including topics such as production and inventory control, scheduling, logistics, and distribution.  Some of my earlier work in this area covered topics such as just-in-time systems, multi-echelon distribution, parallel machine scheduling with major and minor setups, optimal fixture selection for machining rotational parts, and applications of RFID systems.

Some years ago, I did some interesting work with my colleague Andrew Schaefer (now at Rice University) on designing and managing remnant inventory supply chains, which are found in areas including (but not limited to) steel, aluminum, paper, textiles, fiber-optic cable and lumber, where remnants from prior cutting operations are stored in inventory and can be used to satisfy (stochastic) demand as it comes in.  We worked on combining both the design aspect of where facilities should be optimally located and the operational aspect of how they should service demand. I also worked with Kim Needy at the University of Arkansas and PhD student Natalie Scala (now a faculty member at Towson University) on a data-driven, engineering management approach to managing spare parts inventories in the nuclear power sector.  Finally, I collaborated for a number of years with my ex-colleague Bryan Norman (now at Texas Tech) and several graduate students (Sheng-I Chen, Nazanin Esmaili, Jung Lim and Yuwen Yang) on the health care supply chain (more on some of this in the section below...).  I also worked briefly on the so-called "unconventional" energy sector, with a focus on fracking and the shale gas supply chain.

Here's a partial list of some of my relevant publications in the broad area of operations, in case you're interested.

Applications of IE/OR to Healthcare

This is an area in which I have been working for the last ten to twelve years.  In one initiative within the Veteran's Engineering Resource Center (VERC, funded by the Veteran's Administration), I worked with my ex-IE colleague Bryan Norman on various operational problems within the VA System, ranging from improving Veterans' access to healthcare, to managing inventories of medical supplies and pharmaceuticals, to better matching of demand and capacity.  Earlier I was part of another VERC effort, working with another ex-IE colleague, Andrew Schaefer, and a large team on a project to more efficiently schedule the operating room suite in the VA Pittsburgh hospital. The second area in healthcare delivery that I have been involved with is global health and the WHO-EPI vaccine distribution chain.  This began as the HERMES project (funded by the Bill & Melinda Gates Foundation) where Bryan and I worked with a team of people from  the Graduate School of Public Health (led by Bruce Lee - now at CUNY) and the Pittsburgh Supercomputing Center (led by Shawn Brown), on developing a detailed simulation model of the WHO-EPI vaccine supply chain in developing countries, with a focus on improving the efficiency with which vaccines are delivered to the final recipients.  This eventually led to a couple of different NSF funded grants (one with Bruce, Bryan and another IE colleague, Lisa Maillart, and one a solo effort) on improving clinic operations with the goal of reducing vaccine waste and increasing coverage, and more recently on redesigning the vaccine distribution chain and its operation so as to increase coverage and reduce waste. I am also currently working with a large team of people from IE, Pitt's medical school, Strathmore University in Kenya and several others on a project to improve the entire blood transfusion continuum in Kenya, from collection to delivery. 

Here is a partial list of some of relevant publications.

Geometric Programming

Geometric Programming (GP) is a nonlinear optimization technique for problems with polynomial objective and constraint functions, and has a very elegant theory as well as attractive structural properties. Unfortunately, there has been a misconception that GP requires a very rigid format and that it has very limited applicability in practice. I have been working on a linear reformulation of the GP primal dual pair - this was work that I did with Dennis Bricker at the University of Iowa many years ago. In the reformulation, the primal is stated as a semi-infinite LP, while the dual is a generalized LP. The reformulation leads to a very robust dual-based column generation algorithm that works well on a wide variety of GP problems with virtually no computational difficulties. If you are interested, I have available a list of references of some of my publications in this area; you may also contact me directly if you can't locate the papers, and I'll be happy to send you copies/reprints! I also have the code for the algorithm if you have posynomial GP problems that you need to solve, or if you'd just like to play with the software - it runs on any desktop computer.  The whole system is stored in a file called GPINSTAL.EXE that you may download. This file is self extracting and contains the object file along with instructions and a couple of sample data files - just ftp the file (in binary mode) and run it.


This is another area in which I did a fair amount of work with my ex-colleague Dr. Mainak Mazumdar, although I have not done much in the area for quite a few years now. Our goal was to develop minimum cost system-based component test plans for demonstrating the reliability of a system of different components in various configurations. There are numerous advantages to testing the individual components of a complex system in order to verify system reliability, as opposed to assembling the entire system and then testing it - cost and convenience are the most obvious. However, it is not clear how best this can be done - both from the perspective of the statistical properties of the system and its components, as well as cost. There are lots of challenging and interesting issues that arise from this problem, and the solution techniques encompass a unique blend of probability / statistics and mathematical programming. 

Another topic that I worked on with S.V. Majety, a former doctoral student of mine, is optimal reliability design. Here we try to allocate reliability (and as a special case, redundancy) among the various components and subsystems that make up an arbitrary system so that the total cost of the system is minimized while meeting a specified value for reliability (or reliability is maximized while costs are within some budget). In particular we looked at the case where cost is not necessarily some closed form function of reliability, but rather, cost and reliability appear as discrete data sets. We formulated the problem as an integer program and worked on developing suitable techniques to solve these.

Again, if you are interested here's a list of publications that I have in the reliability area.


[Main | Teaching | Research | Links | Personal ]