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Master of Science in Operations Research (MSOR)

The Master of Science in Operations Research prepares you for careers as research and development engineers and prepares you for a Ph.D.

Last Updated: 12/19/2025 | All information is accurate and still up-to-date

The Master of Science in Operations Research (MSOR) prepares students for careers as research and development engineers in industry. Additionally, it sets the foundation for entering a Ph.D. Program in Operations Research. The MSOR degree requires a minimum of 31 credit hours and the completion of a thesis. Therefore, students gain in-depth knowledge and practical research experience. According to the U.S. Bureau of Labor Statistics, employment of operations research analysts is projected to increase by 23% from 2022 to 2032, surpassing the average growth rate for all occupations.

Master of Science in Operations Research

Core Courses (10 hours)

To earn the Master of Science in Operations Research degree, you must complete OR 601 Seminar in Operations Research for one credit hour. You must attend the seminar throughout your program. The other nine credit hours will come from selecting one core course from three categories:

  • Optimization/Deterministic Models
  • Stochastic Models
  • Data Science and AI (OR PRO TIP: Other graduate-level CSC, STAT or ISE courses may be substituted with approval)
Core Courses 1
Optimization/ Deterministic Models
OR 501 Introduction to Operations Research
OR 504 Introduction to Mathematical Modeling
OR 505 Linear Programming
OR 506 Algorithmic Methods in Nonlinear Programming
OR 531 Dynamic Systems and Multivariable Control I
OR 565 Graph Theory
OR 706 Nonlinear Programming
OR 708 Integer Programming
OR 709 2 Dynamic Programming
OR 719 Vector Space Methods in System Optimization
OR 731 Dynamic Systems and Multivariable Control II
OR 766 Network Flows
Stochastic Models
MA/ST 546 Probability and Stochastic Processes I
MA/ST 747 Probability and Stochastic Processes II
OR 560 Stochastic Models in Industrial Engineering
OR 562 Simulation Modeling
OR 709 2 Dynamic Programming
OR 760 Applied Stochastic Models in Industrial Engineering
OR 761 Queues and Stochastic Service Systems
OR 762 Computer Simulation Techniques
OR 772 Stochastic Simulation Design and Analysis
Data Science and AI
CE 537 Computer Methods and Applications
CSC 505 Design and Analysis of Algorithms
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 537 Statistical Models for Systems Analytics in Industrial Engineering
ISE 538 Practical Machine Learning for Engineering Analytics
OR 579 Introduction to Computer Performance Modeling
ST 516 Experimental Statistics For Engineers II
ST 554 Analysis of Big Data
ST 558 Data Science for Statisticians

1 Special topics courses (such as OR 591/791, ISE 589/789 or MA 591/791) may be counted as appropriate core categories with DGP approval.

2 OR 709 cannot be double-counted for the deterministic and stochastic courses categories

Thesis (3-6 hours)

You must complete a master’s thesis (6 credits of OR 693 and/or OR 695 Master’s Thesis Research). Ideally, your thesis will include publishable research.

Thesis Research
OR 693 Master’s Thesis Research
OR 695 Master’s Thesis Research

Next, form a Graduate Advisory Committee with at least three faculty members. File a committee-approved Plan of Graduate Work with the Graduate School. Your chair or co-chair and another committee member must be OR Faculty. At least one member should represent your minor field of study.

Finally, you must pass a final oral examination conducted by your Advisory Committee. The exam includes, but is not limited to, a “defense of thesis.”

After passing the MSOR final oral examination, each advisory committee member must approve your thesis. Submit the thesis to the Graduate School’s thesis editor, following the Guide for Preparation of Theses and Dissertations.

OR PRO TIP: Know the Graduate School submission deadlines for graduation. Submit your thesis by appointment; call 919.515.2871.

Electives (15-18 hours)

You should choose five additional elective courses from mathematics, engineering, statistics, computer science, or other STEM disciplines. For example, you can select courses in econometrics or data science. Some business courses are also acceptable as electives. OR PRO TIP: Courses used to satisfy the required core courses requirement cannot be used to satisfy the elective course requirement. Direct any questions about electives to the OR Program Specialist, your faculty advisor or academic committee.

Area *Electives
Data Analytics, Stats and Computer Science
BAE 555 R Coding for Data Management and Analysis
ECE 542/CSC 542 Neural Networks
ISE 519 Database Applications in Industrial and Systems Engineering
ISE 535 Python Programming for Industrial and Systems Engineers
ISE 748 Quality Engineering
ST 555 Statistical Programming I
ST 556 Statistical Programming II
ST 558 Data Science for Statisticians
ST 563 Introduction to Statistical Learning
Supply Chain and Logistics
ISE 511 Supply Chain Economics and Decision Making
ISE 513 Humanitarian Logistics
ISE 533 Service Systems Engineering
ISE 552 Design and Control of Production and Service Systems
ISE 553 Modeling and Analysis of Supply Chains
MBA 544 Operations Analysis (Warsing's course)
MBA 548 Analytical Supply Chain Management (Heese's course)
Business/Operations Management
ISE 510 Applied Engineering Economy
ISE 511 Supply Chain Economics and Decision Making
*Courses may appear in multiple areas. Be sure to check special topics (e.g. OR 591, OR 791, ISE 589, ISE 789) which vary semester by semester.

Total Hours (31 hours)

OR PRO TIP: Must have at least 12 credits of OR prefix courses.

OR Minor

To minor in operations research as part of a Master of Science degree, you need three OR courses (9 credits). Additionally, you must have an OR faculty member on your committee.

If an OR course is cross-listed with other departments, register using the OR prefix.

Sample MSOR Pathways

Stochastics

SemesterCourse #1Course #2Course #3Course #4
FallOR 601 (1 credit)ISE 535OR 501OR 560
SpringOR 504OR 562OR 709ST 515
FallEM 538OR 695ST 516

Optimization

SemesterCourse #1Course #2Course #3Course #4
FallOR 601 (1 credit)MA 405OR 501ST 555
SpringOR 504OR 560ST 556
FallISE 537OR 505OR 506OR 695

Supply Chain and Logistics

SemesterCourse #1Course #2Course #3Course #4
FallOR 601 (1 credit)EM 538ISE 511OR 501
SpringISE 552ISE 553OR 562
FallISE 519ISE 754OR 506OR 695

Data Science and AI

SemesterCourse #1Course #2Course #3Course #4
FallOR 601 (1 credit)ISE 535ISE 537OR 504
SpringISE 519MEM 538OR 562OR 693
FallECE 542OR 565OR 695