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Department of Operations Research and Financial Engineering


Robert J. Vanderbei

Departmental Representative

Alain L. Kornhauser

Director of Graduate Studies

Patrick Cheridito


René A. Carmona

Erhan Çinlar

Jianqing Fan

Alain L. Kornhauser

William A. Massey

John M. Mulvey

Warren B. Powell

K. Ronnie Sircar

Robert J. Vanderbei

Associate Professor

Patrick Cheridito

Alexandre W. d'Aspremont

Assistant Professor

Philippe Rigollet

Birgit Rudloff

Ramon van Handel

Associated Faculty

Yacine Aït-Sahalia, Economics

Markus  K. Brunnermeier, Economics

Ingrid C. Daubechies, Mathematics, Applied and Computational Mathematics

Weinan E, Mathematics

Christodoulos A. Floudas, Chemical and Biological Engineering

Sanjeev R. Kulkarni, Electrical Engineering

H. Vincent Poor, Electrical Engineering

Robert E. Schapire, Computer Science

José A. Scheinkman, Economics

Paul D. Seymour, Mathematics

Yakov G. Sinai, Mathematics

Elias M. Stein, Mathematics

John D. Storey, Molecular Biology and Lewis-Sigler Institute for Integrative Genomics

Wei Xiong, Economics

Information and Departmental Plan of Study

Operations research and financial engineering may be considered as the modern form of a liberal education: modern because it is based on science and technology, and liberal in the sense that it provides for broad intellectual development and can lead to many different types of careers. By choosing judiciously from courses in engineering, economics, public policy, and liberal arts, each student may design a program adapted to his or her particular interests.

All students start from a common academic core consisting of statistics, probability and stochastic processes, and optimization. Related courses focus on developing computer skills and exposing students to applications in areas such as finance, operations, transportation, and logistics. Students augment the core program with a coherent sequence of departmental electives. Students may also design specialized programs, which must be reviewed and approved by their academic adviser and the departmental representative. Students often draw on courses from economics, computer science, applied mathematics, civil and environmental engineering, mechanical engineering, and the Woodrow Wilson School of Public and International Affairs. Requirements for study in the department follow the general requirements for the School of Engineering and Applied Science and the University.

Program of Study

The student's program is planned in consultation with the departmental representative and the student's adviser and requires a year-long thesis or a one-semester senior project. With departmental approval, the exceptional student who wishes to go beyond the science and engineering requirements may select other courses to replace some of the required courses in order to add emphasis in another field of engineering or science or to choose more courses in the area of study. Suggested plans of study and areas of concentration are available from the departmental representative.

In addition to the engineering school requirements, there are three components to the curriculum:

1. The core requirements (six courses). These form the intellectual foundation of the field and cover statistics, probability, stochastic processes, and optimization, along with more advanced courses in mathematical modeling.

2. Departmental electives (eight or nine courses). These are courses that either extend and broaden the core, or expose the student to a significant problem area or application closely related to the core program.

3. Senior independent research. A one-semester project or a full-year thesis involving an application of the techniques in the program applied to a topic that the student chooses in consultation with a faculty adviser.

Core requirements (six courses):

ORF 245 Fundamentals of Engineering Statistics
ORF 307 Optimization
ORF 309 Probability and Stochastic Systems
ORF 335 Introduction to Financial Mathematics
ORF 405 Regression and Applied Time Series
ORF 411 Operations and Information Engineering

Departmental electives (eight or nine courses, if a one-semester project is selected): the departmental electives represent courses that further develop a student's skills in mathematical modeling either by a more in-depth investigation of core disciplines, applying these skills in specific areas of application, or learning about closely related technologies. Students must choose eight or nine courses, as appropriate, with the following constraints:

1. There must be at least one 300-level math course from the following:

APC 350 Introduction to Differential Equations
MAE 305 Mathematics in Engineering I
MAE 306 Mathematics in Engineering II
MAT 303 Ordinary Differential Equations
MAT 304 Introduction to Partial Differential Equations
MAT 306 Introduction to Graph Theory
MAT 307 Combinatorial Mathematics
MAT 308 Theory of Games
MAT 314 Introduction to Real Analysis
MAT 390 Probability Theory
MAT 391 Random Processes

2. There must be at least two courses from the Department of Operations Research and Financial Engineering (ORF).

3. There can be no more than three courses from any one department (excluding ORF).

A list of all other departmental electives may be found in the departmental undergraduate academic guide; see the department website.

Students in the department often participate in the following certificate programs and laboratories:

Certificate in Finance. The department cooperates with the Bendheim Center in Finance, which offers a certificate program in finance. 

Certificate Program in Engineering and Management Systems. The department sponsors a certificate program for students majoring in other departments who complete a significant part of the core of the undergraduate program. 

Certificate in Applied and Computational Mathematics. Students seeking a strong mathematical foundation can combine courses from the department with supporting courses which develop more fundamental mathematical skills. 

The department maintains several research laboratories which may be used as part of undergraduate research projects.

Computational and Stochastic Transportation and Logistics Engineering Laboratory. The CASTLE Laboratory works on problems in dynamic resource management with ongoing projects in chemical distribution, railroads, trucking, and the airlift mobility command. Through this lab, students gain access to data and specialized tools to aid them in their research into transportation and logistics.

Financial Engineering Laboratory. This facility provides students with access to specialized software packages and to financial data and news services. Research in the laboratory is concerned with the analysis of the various forms of financial risk and the development of new financial instruments intended to control the risk exposure of insurance and reinsurance companies.

Transportation Information and Decision Engineering Center. The TIDE Center conducts research on information and decision engineering technologies and on how these technologies can be used to improve transportation-related decision making. Included in TIDE is Princeton Autonomous Vehicle Engineering (PAVE), an extracurricular undergraduate activity focused on the implementation of advanced sensing and control technologies for optimal autonomous decision making in vehicles. The current objective is the development of an autonomous vehicle that can pass the New Jersey State Driving Test.


ORF 105 The Science and Technology of Decision Making (also EGR 106)   Not offered this year QR

An individual makes decisions every day. In addition, other people are making decisions that have an impact on the individual. In this course we will consider both how these decisions are made and how they should be made. In particular, we will focus on the use of advanced computing and information technology in the decision-making process. Staff

ORF 245 Fundamentals of Engineering Statistics (also EGR 245)   Fall, Spring QR

A study of fundamentals of statistical methods and their applications in engineering. Basic concepts of probability, discrete and continuous distributions, sampling and quality control, statistical inference, empirical models, and least squares. Three lectures. Open to freshmen. P. Rigollet

ORF 307 Optimization (also EGR 307)   Spring

Model formulation, analysis, and optimization of deterministic systems. Introduction to quantitative methods: linear programming, duality theory, large-scale mathematical programs, and network analysis. Emphasis will be on applications to problem areas such as allocation of resources, transportation systems, scheduling, capital budgeting, and network problems. Two 90-minute lectures. Prerequisite: MAT 202. A. d'Aspremont

ORF 309 Probability and Stochastic Systems (also EGR 309/MAT 309)   Fall

An introduction to probability and its applications. Random variables, expectation, and independence. Poisson processes, Markov chains, Markov processes, and Brownian motion. Stochastic models of queues, communication systems, random signals, and reliability. Prerequisite: MAT 201, 203, 217, or instructor's permission. E. Çinlar

ORF 311 Optimization under Uncertainty   Fall

A survey of quantitative approaches for making optimal decisions involving uncertainty and complexity including decision trees, Monte Carlo simulation, and stochastic programming. Forecasting and planning systems are integrated. Applications in financial planning. Prerequisites: 307 or MAT 305, and 309. Two 90-minute classes. J. Mulvey

ORF 322 Human-Machine Interaction (see PSY 322)

ORF 335 Introduction to Financial Mathematics (also ECO 364)   Spring QR

Financial engineers design and analyze products that improve the efficiency of markets and create mechanisms for reducing risk. This course introduces the basics of financial mathematics: the notions of arbitrage and risk-neutral probability measure are developed in the case of discrete models; Black-Scholes theory is introduced in continuous-time models, and interest rate derivatives and the term structure of interest rates are discussed. Prerequisites: 309, ECO 100, and MAT 104. R. Sircar

ORF 374 Special Topics in Operations Research and Financial Engineering   Not offered this year

A course covering special topics in operations research or financial engineering. Subjects may vary from year to year. Staff

ORF 375 Independent Research Project   Fall

Independent research or investigation resulting in a report in the student's area of interest under the supervision of a faculty member. Open to sophomores and juniors. A. Kornhauser

ORF 376 Independent Research Project   Spring

Independent research or investigation resulting in a report in the student's area of interest under the supervision of a faculty member. Open to sophomores and juniors. A. Kornhauser

ORF 401 Electronic Commerce   Spring

Electronic commerce is broadly defined as the buying and selling of goods using electronic transaction processing technologies. This course considers the technologies themselves, as well as various economic and financial issues associated with their use. Two 90-minute lectures. A. Kornhauser

ORF 405 Regression and Applied Time Series   Fall

Regression analysis: least squares and robust alternatives, nonparametric techniques (splines, projection pursuit, and neural network). Time-series: trends, seasonal effects, clinical models, state space models. Includes a final project in the form of a realistic forecasting game involving portfolio management and economic time-series data. Prerequisites: 245 and MAT 202. R. Carmona

ORF 406 Statistical Design of Experiments   Not offered this year

Major methods of statistics as applied to the engineering and physical sciences. The central theme is the construction of empirical models, the design of experiments for elucidating models, and the applications of models for forecasting and decision making under uncertainty. Three lectures. Prerequisite: 245 or equivalent. Staff

ORF 407 Fundamentals of Queueing Theory   Spring QR

An introduction to the fundamental results of queueing theory. Topics covered include: the classical traffic; offered load; and loss and delay stochastic models for communication systems. Through concrete examples and motivations, the theory of Markov chains, Poisson processes, and Monte Carlo simulation are discussed. Fundamental queueing results such as the Erlang blocking and delay formulae, Little's law and Lindley's equation are presented. Applications are drawn from communication network systems, inventory management, and optimal staffing. Prerequisite: 309 or equivalent. Two 90-minute lectures. W. Massey

ORF 409 Introduction to Monte Carlo Simulation   Fall

An introduction to the uses of simulation and direct computation in analyzing stochastic models and interpreting real phenomena. Deals with generating discrete and continuous random variables, stochastic ordering, the statistical analysis of simulated data, variance reduction techniques, statistical validation techniques, nonstationary Markov chains, and Markov chain Monte Carlo methods. Applications are drawn from problems in finance, manufacturing, and communication networks. Prerequisite: 309. Two 90-minute classes. W. Massey

ORF 411 Operations and Information Engineering   Fall

The modeling of complex systems under uncertainty through the control of physical, financial, and informational resources. Students learn how to model stochastic, dynamic systems, using the contextual domain of resource allocation arising in settings such as energy, finance, health, and human resource management. Policy optimization is introduced as a mechanism for controlling systems, along with information exchange and efficient collection of new information. Prerequisites: 245, 307 and 309, or equivalents. Two 90 minute lectures. W. Powell

ORF 417 Dynamic Programming   Not offered this year

An introduction to stochastic dynamic programming and stochastic control. The course deals with discrete and continuous-state dynamic programs, finite and infinite horizons, stationary and nonstationary data. Applications drawn from inventory management, sequential games, stochastic shortest path, dynamic resource allocation problems. Solution algorithms include classical policy and value iteration for smaller problems and stochastic approximation methods for large-scale applications. Prerequisites: 307 and 309. Staff

ORF 418 Optimal Learning   QR

Addresses the problem of collecting information used to estimate statistics or fit a model which is then used to make decisions. Of particular interest are sequential problems where decisions adapt to information as it is learned. The course introduces students to a wide range of applications, demonstrates how to express the problem formally, and describes a variety of practical solution strategies. Prerequisite: ORF 245, ORF 309. Two 90-minute lectures. W. Powell

ORF 435 Financial Risk Management   Fall

This course covers the basic concepts of modeling, measuring and managing financial risks. Topics include mean-variance portfolio theory, fixed-income securities, options pricing, Greeks, risk measures, and utility functions. Prerequisites: 245, 335 or ECO 465 (concurrent enrollment is acceptable) or instructor's permission. Two 90-minute lectures. B. Rudloff

ORF 467 Transportation Systems Analysis   Fall

Operations research in transportation and logistics. Vehicle routing and scheduling, warehouse location, network flow models in transportation, set partitioning solutions to vehicle and crew assignment problems, fixed-charge problems and network equilibrium models. Emphasis placed on the theory and implementation of algorithms for large, specially structured problems. Two 90-minute lectures. Prerequisites: linear programming and network algorithms. A. Kornhauser

ORF 474 Special Topics in Operations Research and Financial Engineering   Spring

A course covering one or more advanced topics in operations research and financial engineering. Subjects may vary from year to year. Three classes Staff

ORF 478 Senior Thesis   Spring

A year-long, independent study of a significant problem in operations research or financial engineering. Topic proposals must be submitted during the spring of junior year and must be accepted by the ORFE departmental representative. A written report is required at the end of each term, though enrollment is only in the spring term when a double-credit grade is awarded. Students give an oral presentation at the end of the spring term. Students must make acceptable progress in the fall term in order to continue in the spring. Fulfills the departmental independent work requirement for seniors. A. Kornhauser

ORF 479 Senior Project  

A one-semester project that fulfills the departmental independent work requirement for concentrators. Topics are chosen by students in consultation with members of the faculty. A written report is required at the end of the term. A. Kornhauser

ORF 491 High-Tech Entrepreneurship (see ELE 491)