Applicants should have a working knowledge of linear algebra, calculus, probability and statistical inference. Applicants should also have a strong analytical background, as acquired by an undergraduate major in engineering, mathematical sciences, computer science or economics, or by relevant work experience and industrial achievements following undergraduate education. Masters students are required to take a comprehensive oral qualifying exam before graduation.
Application Requirements:
Students are required
to take the GRE general test, and submit a resume, recent
transcripts, and three letters of recommendation. Applicants can apply
online at http://gradstudy.rutgers.edu
.
Options:
Masters in OR with thesis (8 courses + 6 research credits to
complete
thesis) = 30 credits.
Masters in OR without thesis (10 courses) = 30 credits.
Students choosing the non-thesis option must write a satisfactory essay
for the
Master's degree.
Required Core Courses:
Fall:
Theory of Linear Optimization
Stochastic Models
Design & Analysis of Computer Algorithms
Spring:
Computational O.R.
Integer Programming
Networks & Combinatorial Optimization
Case Studies
Masters Program: Elective
courses
Computer Science (16/198)
16:198:510 Numerical Analysis
16:198:513/514 Design & Analysis of Data Structures &
Algorithms I,
II
16:198:521 Linear Programming
16:198:522 Network & Comb
Optimization
16:198:524 Non-Lin Programming
Algorithms
16:198:526 Advanced Numerical Analysis
16:198:528 Parallel Numerical
Computing
16:198:529 Computational Geometry
16:198:535 Pattern Recognition
Theory &
Application
16:198:536 Machine Learning
16:198:538 Complexity of Computation
16:198:541 Database Systems
Economics (16/220)
16:220:500 Mathematical Methods for
Microeconomics
16:220:501/502 Microeconomics I, II
16:220:503 Mathematical Methods for
Microeconomics
16:220:506 Advanced Economic
Statistics
16:220:507/508 Econometrics I, II
16:220:545 Uncertainty &
Imperfect
Information
16:220:546 Topics in Game
Theory
Industrial & Systems Engineering (16/540)
16:540:510 Deterministic Models in IE
16:540:515 Stochastic Models in IE
16:540:520 Supply Chain Engineering
16:540:522 Case Study Supply Chain
16:540:530 Forecast & Time
Series Analysis
16:540:535 Network Applications in
Industrial
& Systems Engineering
16:540:555 Simulation of Production
Systems
16:540:560 Production Analysis
16:540:564 Supply Chain Eng II
16:540:565 Facilities Planning &
Design
16:540:568 Automation & Computer Integrated Manufacturing
16:540:575 Advanced Engineering
Economics I
16:540:585 System Reliability Engineering I
16:540:616 Advanced Stochastic Model
ISE
16:540:660 Inventory Control
16:540:665 Theory of Scheduling
16:540:685 System Reliability Engineering II
Mathematics (16/640 & 642)
16:640:501 Theory of Functions of a
Real
Variable
16:640:502 Theory of Functions of a
Real
Variable
16:640:503 Theory of Functions of a
Complex
Variable I
16:640:504 Theory of Functions of a
Complex
Variable II
16:640:507 Functional Analysis
16:640:508 Functional Analysis
16:640:517 Partial Differential Equations I
16:642:527 Methods Applied Math
16:642:528 Methods Applied Math
16:642:550 Linear Algebra &
Applications
16:642:573/574 Numerical Analysis
16:642:581 Applied Graph Theory
16:642:582/583 Combinatorics I, II
16:642:585 Mathematical Models of
Social &
Policy Problems
16:642:587 Selected Topics in
Discrete
Mathematics
16:642:621 Math Finance I
Operations Research (16/711)
16:711:517 Computational OR
16:711:531 Actuarial
16:711:553 Boolean &
Pseudo-Boolean Functions
16:711:555 Stochastic Programming
16:711:556 Queueing
Theory
16:711:557 Dynamic Programming &
Markov
decision Processes
16:711:613 Game Theory
16:711:612 Nonlinear Programming
16:711:611 Semi-Definite Programming
16:711:631 Financial Mathematics
16:711:601/602 Seminar in Operations Research
16:711:695-699 Independent Study in Operations Research
16:711:701/702 Research
Statistics (16/960)
16:960:540/541 Statistical Quality Control I, II
16:960:542 Life Data Analysis
16:960:554 Applied Stochastic
Processes
16:960:563 Regression Methods
16:960:565 Applied Time Series
Analysis
16:960:567 Applied Multivariate Analysis
16:960:580 Basic Probability
16:960:582 Intro Methods &
Theory of
Probability
16:960:586/587 Interpretation of Data I, II
16:960:588 Data Mining
16:960:590 Design of Experiments
16:960:591 Advanced Design of
Experiments
16:960:592 Theory of Probability
16:960:593 Theory of Statistics
16:960:652/653 Advanced Theory of Statistics
16:960:654 Stochastic Processes
16:960:663 RegressionTheory
16:960:680/681 Advanced Probability Theory I. II
16:960:668 Bayesian Data Analysis
16:960:689 Sequential Methods
Finance (26/390)
26:390:571,572 Survey of Financial Theory
26:390:662 Investment Analysis &
Portfolio
Theory
Operations Research (26/711)
26:711:561 Intro to Math Economics
26:711:652 Non-Linear
Programming
Statistics (26/960)
26:960:580 Stochastic
Processes
16/Graduate School,
26/