PhD Operations, Information, and Technology Courses
OIT 601. Fundamentals of OIT
The goal of this course is to provide first-year Ph.D. students in OIT with sufficient fundamentals to subsequently take advanced research seminars. The course covers the very basics of six topics: queuing theory, inventory theory, multi-echelon inventory theory, game theory, stochastic dynamic programming and econometrics. Lectures will be given by advanced Ph.D. students in OIT.
OIT 602. Dynamic Pricing and Revenue Management I
In tandem with OIT 603, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217-218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially in the realm of airline revenue management.
OIT 603. Dynamic Pricing and Revenue Management II
In tandem with OIT 602, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217-218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially involving customized pricing of financial services. OIT 602 is not a prerequisite for OIT 603 but is highly recommended.
OIT 641. Introduction to OIT Research
This course introduces students to research areas in the operations, information, and technology field. It focuses on the structure of models and approaches that are a part of the definition of the OIT field. Topics vary from year to year, but include special features of information products, pricing and incentives in queuing models, the effects of information technology on industrial organization, models of inter-firm collaboration and supply chain management. Not offered in 2008-09.
OIT 655. Foundations of Supply Chain Management
This course provides an overview of research in supply chain management (SCM). It has three parts. The first part reviews basic tools of SCM research through selected readings in economics, IT and operations research. The second part reviews the literature in SCM, covering topics such as inventory models, information sharing, information distortion, contract design, value of integration, performance measurement, risk management, and the use of markets for procurement. The last part is devoted to recent advances in SCM research.
OIT 659. Operations Models in Homeland Security
In this course, we review the recent operations literature on homeland security. Topics include bioterrorism, pandemic influenza, nuclear security at ports and in cities, the biometric aspects of the US-VISIT program, the detention and removal of illegal aliens, suicide bombers, and electric power security. Not offered in 2008-09.
OIT 662. Workshop in Operations/Information Systems
This workshop covers current research topics and results in operations, information, and technology. Topics change every year. Not offered in 2008-09.
OIT 663. Methods of Operations/Information Systems
This course covers basic analytical tools and methods that can be used in research in operations and information systems. The emphasis is on foundations of stochastic inventory theory. Basic topics include convexity, duality, induced preference theory, and structured probability distributions. Much of the course is devoted to Markov decision processes, covering finite and infinite horizon models, proving the optimality of simple policies, bounds and computations, and myopic policies.
OIT 664. Stochastic Networks
Processing network models may be used to represent service delivery systems, multi-stage manufacturing processes, or data processing networks. The first half of this two-unit course consists of lectures on performance analysis (e.g., estimating congestion and delay) for classical product-form networks and for Brownian networks. The second half consists of student presentations of recent papers on managing processing networks, typically with game-theoretic aspects. Prerequisites: Statistics 217 and 218, or consent of instructor; some prior exposure to stochastic models in general, and queuing theory in particular, is useful but not essential. Not offered in 2008-09.
OIT 665. Seminar on Information-Based Supply Chain Management
This seminar will highlight the research advances on the use of information technology in supply chain management. Such usage has helped companies sharing information to coordinate their supply chain and to realign their incentives. It has also helped reduce the so-called bullwhip effect. Latest information technology like RFID (radio-frequency identification) has also enabled visibility and structural changes that result in significant supply chain performance enhancements. This seminar will focus on the modeling approaches used by researchers that tried to capture the values and potentials of such applications. Not offered in 2008-09.
OIT 667. Revenue Management
Systems for revenue management—also called "yield management" or "revenue optimization"—combine the use of information technology, statistical forecasting, and mathematical optimization to make tactical decisions about pricing and product availability. A familiar example is the passenger airline industry, where a carrier may sell seats on the same flight at many different fares, with fare availability changing as time advances and uncommitted capacity declines. This course will focus on the mathematical models that underlie contemporary revenue management practice, and on current research areas. The format will mix lecture and discussion with presentation of papers from the research literature. Prerequisite knowledge includes microeconomics, probability theory, optimization theory and dynamic programming, each at the level of an introductory graduate course. Not offered in 2008-09.
OIT 669. Doctoral Management Science Seminar
This course introduces the students to research concepts, models and approaches in the area of Operations, Information and Technology (OIT). The course covers both modeling and empirical approaches, with papers from the entire OIT spectrum. The course will use a combination of (1) lectures, (2) a discussion of homework assignments, and (3) critical reading of research papers in the field. Not offered in 2008-09.
OIT 670. Applied Dynamic Optimization
This course provides an introduction to the methods of dynamic programming, Markov decision processes, optimal control, and stochastic control, with particular emphasis on business applications. Application domains include manufacturing, supply chains, economics, and finance. While there are no prerequisites beyond basic probability theory and optimization, the course emphasizes topics that are not usually covered in a first course on dynamics programming or Markov decision processes, such as continuous time systems and general state spaces. Not offered in 2008-09.
