Master of Science in Operations Research

The School of Industrial and Systems Engineering (ISYE) offers eight master's degrees:

  • Master of Science in Industrial Engineering (MS IE);
  • Master of Science in Operations Research (MS OR);
  • Master of Science in Supply Chain Engineering (MS SCE);
  • Master of Science in Statistics (MS STAT);
  • Master of Science in Health Systems (MS HS);
  • Master of Science in Quantitative and Computational Finance (MS QCF);
  • Master of Science in International Logistics (MS IL) that is part of the executive program; and
  • Master of Science in Computational Science and Engineering (MS CSE).

Three of these programs are interdisciplinary:

  • MS QCF (joint with School of Mathematics, College of Business),
  • MS STAT (joint with School of Mathematics) and
  • MS SCE (joint with College of Computing, School of Mathematics).

All proposed master's degree programs require thirty semester credit hours with the exception of MS IL and MS QCF (thirty-six credit hours) and MS HS (thirty-three credit hours). None of these MS programs contains a thesis option.

A student seeking a master's degree must have a bachelor's degree and typically one earned in engineering, science, mathematics, or some other field that provides an adequate background for the successful completion of one of ISyE's programs. Students having backgrounds from unaccredited degree programs or in programs that are found lacking in relative substance can expect to first take preliminary coursework in order to elevate their preparation to the level required. The prerequisite coursework for the various master's degrees includes strong performance in probability, statistics, linear algebra, and calculus.

Every MS curriculum is based on core classes offered from the School of ISyE, as well as electives offered by ISyE and other Georgia Tech schools in engineering and science. The MS SCE, MS QCF, and MS IL are professional degree programs with separate curriculums from the other regular MS degrees.

MS Human-Integrated Systems

Program Requirements

Core
ISYE 6644Simulation3
ISYE 6650Probabilistic Models and Their Applications3
ISYE 6669Deterministic Optimization3
Statistics and Data Science Elective3
Mathematical Statistics I
Theoretical Statistics
Statistical Modeling and Regression Analysis
Advanced Statistical Modeling
Linear Statistical Models
Computational Data Analysis: Learning, Mining, and Computation
Design and Analysis of Experiments
Advanced Design of Experiments
Computational Statistics
Introduction to Theory and Practice of Bayesian Statistics
Advanced Statistical Inference I
Testing Statistical Hypotheses
Algorithms and Computation Elective3
Computational Methods in Optimization
Computational Data Analysis: Learning, Mining, and Computation
Special Topics in Operations Research (Constraint Programming)
Computability, Algorithms, and Complexity
Computational Complexity Theory
Design and Analysis of Algorithms
Computational Science and Engineering Algorithms
Technical Electives (Choose 3)9
Economic Decision Analysis
Scheduling Theory
Public Impact Applications of Operations Research and Management Science
Monte Carlo Methods
Linear Optimization
Discrete Optimization
Nonlinear Optimization
Stochastic Optimization
Computational Methods in Optimization
Stochastic Processes I
Stochastic Processes II
Simulation Theory and Methods
Production and Service Systems Engineering
Logistics Systems Engineering
Special Topics in Operations Research (Inventory Theory)
Special Topics in Operations Research (Constraint Programming)
Special Topics in Operations Research (Stochastic Programing)
Special Topics in Operations Research (Game Theory)
Special Topics in Operations Research (Infrastructure Optimization)
Breadth Electives (Choose 2)6
Advanced Engineering Economy
Manufacturing Systems
Production and Service Systems Engineering
Warehousing Systems
Transportation and Supply Chain Systems
Logistics Systems Engineering
Special Topics in Operations Research (Inventory Theory)
Statistical Methods for Manufacturing Design and Improvement
Time Series Analysis
Nonparametric Data Analysis
Design and Analysis of Experiments
Advanced Design of Experiments
Statistical Modeling and Regression Analysis
Advanced Statistical Modeling
Linear Statistical Models
Computational Statistics
Introduction to Theory and Practice of Bayesian Statistics
Data Mining and Statistical Learning
Special Topics in Operations Research (Mathematics of Operations Research)
Computational Data Analysis: Learning, Mining, and Computation
Data and Visual Analytics
Modeling and Simulation: Foundations and Implementation
Analysis I
Real Analysis I
Real Analysis II
Graph Theory and Combinatorial Structures
Probability I
Probability II
Numerical Linear Algebra
Advanced Statistical Inference I
Testing Statistical Hypotheses
Parallel and Distributed Simulation Systems
Computability, Algorithms, and Complexity
Computational Complexity Theory
Design and Analysis of Algorithms
Total Credit Hours30

Up to six (6) credits of 4000-level courses may be used towards the degree, subject to the approval of the ISyE Director of Master's Programs

Practicum Track Requirements

Core
ISYE 6650Probabilistic Models and Their Applications3
ISYE 6669Deterministic Optimization3
Statistics and Data Science Elective3
Mathematical Statistics I
Theoretical Statistics
Statistical Modeling and Regression Analysis
Advanced Statistical Modeling
Linear Statistical Models
Computational Data Analysis: Learning, Mining, and Computation
Design and Analysis of Experiments
Advanced Design of Experiments
Computational Statistics
Introduction to Theory and Practice of Bayesian Statistics
Advanced Statistical Inference I
Testing Statistical Hypotheses
Algorithms and Computation Elective3
Computational Methods in Optimization
Computational Data Analysis: Learning, Mining, and Computation
Special Topics in Operations Research (Constraint Programming)
Computability, Algorithms, and Complexity
Computational Complexity Theory
Design and Analysis of Algorithms
Computational Science and Engineering Algorithms
Technical Electives (Choose 3)9
Economic Decision Analysis
Scheduling Theory
Public Impact Applications of Operations Research and Management Science
Monte Carlo Methods
Linear Optimization
Discrete Optimization
Nonlinear Optimization
Stochastic Optimization
Computational Methods in Optimization
Stochastic Processes I
Stochastic Processes II
Simulation Theory and Methods
Production and Service Systems Engineering
Logistics Systems Engineering
Special Topics in Operations Research (Inventory Theory)
Special Topics in Operations Research (Constraint Programming)
Special Topics in Operations Research (Stochastic Programing)
Special Topics in Operations Research (Game Theory)
Special Topics in Operations Research (Infrastructure Optimization)
Breadth Electives (Choose 2)6
Advanced Engineering Economy
Manufacturing Systems
Production and Service Systems Engineering
Warehousing Systems
Transportation and Supply Chain Systems
Logistics Systems Engineering
Special Topics in Operations Research (Inventory Theory)
Statistical Methods for Manufacturing Design and Improvement
Time Series Analysis
Nonparametric Data Analysis
Design and Analysis of Experiments
Advanced Design of Experiments
Statistical Modeling and Regression Analysis
Advanced Statistical Modeling
Linear Statistical Models
Computational Statistics
Introduction to Theory and Practice of Bayesian Statistics
Data Mining and Statistical Learning
Special Topics in Operations Research (Mathematics of Operations Research)
Computational Data Analysis: Learning, Mining, and Computation
Data and Visual Analytics
Modeling and Simulation: Foundations and Implementation
Analysis I
Real Analysis I
Real Analysis II
Graph Theory and Combinatorial Structures
Probability I
Probability II
Numerical Linear Algebra
Advanced Statistical Inference I
Testing Statistical Hypotheses
Parallel and Distributed Simulation Systems
Computability, Algorithms, and Complexity
Computational Complexity Theory
Design and Analysis of Algorithms
Internship Preparation Elective 13
Economic Decision Analysis
Simulation
Energy Technology and Policy
Practicum
COOP/INTN/ISYE Practicum
Total Credit Hours30

Up to six (6) credits of 4000-level courses may be used towards the degree, subject to the approval of the ISyE Director of Master's Programs 

1

ISYE Special Topics courses, as appropriate

BS/MS OPTION

The BSMS Option allows eligible students to double count a maximum of 6 credit hours toward undergraduate and graduate requirements while still completing all other program requirements to earn both degrees. 

BS in Industrial Engineering students with a GPA of 3.5 or higher who have taken ISYE 3133 and ISYE 3232 are eligible to apply to utilize the BSMS Option. BSIE students must also graduate with a GPA of 3.5 or higher in order to utilize the BSMS Option.

It is typical for students to use 6 hours from the BSIE concentration electives to count as Core Courses or Technical Electives for the MS in Operations Research degree. Students will need to consult with an advisor to indicate which courses are sharing with the graduate degree in DegreeWorks.