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.
Program Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Core | ||
| ISYE 6644 | Simulation | 3 |
| ISYE 6650 | Probabilistic Models and Their Applications | 3 |
| ISYE 6669 | Deterministic Optimization | 3 |
| Statistics and Data Science Elective | 3 | |
| Mathematical Statistics I | ||
| Theoretical Statistics | ||
| Statistical Modeling and Regression Analysis | ||
or ISYE 7401 | Advanced Statistical Modeling | |
or MATH 6266 | Linear Statistical Models | |
| Computational Data Analysis: Learning, Mining, and Computation | ||
| Design and Analysis of Experiments | ||
or ISYE 7400 | Advanced Design of Experiments | |
| Computational Statistics | ||
| Introduction to Theory and Practice of Bayesian Statistics | ||
| Advanced Statistical Inference I | ||
| Testing Statistical Hypotheses | ||
| Algorithms and Computation Elective | 3 | |
| 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 | ||
or ISYE 7201 | Production and Service Systems Engineering | |
| Warehousing Systems | ||
| Transportation and Supply Chain Systems | ||
or ISYE 7203 | 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 | ||
or ISYE 7400 | Advanced Design of Experiments | |
| Statistical Modeling and Regression Analysis | ||
or ISYE 7401 | Advanced Statistical Modeling | |
or MATH 6266 | 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 Hours | 30 | |
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
| Code | Title | Credit Hours |
|---|---|---|
| Core | ||
| ISYE 6650 | Probabilistic Models and Their Applications | 3 |
| ISYE 6669 | Deterministic Optimization | 3 |
| Statistics and Data Science Elective | 3 | |
| Mathematical Statistics I | ||
| Theoretical Statistics | ||
| Statistical Modeling and Regression Analysis | ||
or ISYE 7401 | Advanced Statistical Modeling | |
or MATH 6266 | Linear Statistical Models | |
| Computational Data Analysis: Learning, Mining, and Computation | ||
| Design and Analysis of Experiments | ||
or ISYE 7400 | Advanced Design of Experiments | |
| Computational Statistics | ||
| Introduction to Theory and Practice of Bayesian Statistics | ||
| Advanced Statistical Inference I | ||
| Testing Statistical Hypotheses | ||
| Algorithms and Computation Elective | 3 | |
| 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 | ||
or ISYE 7201 | Production and Service Systems Engineering | |
| Warehousing Systems | ||
| Transportation and Supply Chain Systems | ||
or ISYE 7203 | 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 | ||
or ISYE 7400 | Advanced Design of Experiments | |
| Statistical Modeling and Regression Analysis | ||
or ISYE 7401 | Advanced Statistical Modeling | |
or MATH 6266 | 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 1 | 3 | |
| Economic Decision Analysis | ||
| Simulation | ||
| Energy Technology and Policy | ||
| Practicum | ||
| COOP/INTN/ISYE Practicum | ||
| Total Credit Hours | 30 | |
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.