Operations Research Curriculum | NC State OR

• You will discuss operations research problems in seminars. Additionally, you will analyze cases and write reports. If you are a graduate student with a minor or major in operations research, you must attend throughout your residence.
• Hours: 1

• Operations Research (OR) involves developing and applying advanced analytical methods to aid complex decisions. Throughout this course, you will learn to apply various analytical methods to diverse applications. These methods include linear and mixed-integer programming, nonlinear and combinatorial optimization, network models, and machine learning. The focus will be on translating real-world problems into models and applying computational procedures and data to aid decision-making. Applications include improving production and service systems, healthcare delivery, and transportation systems. OR also helps make better decisions in sports, marketing, and project management. Prerequisites for this course include undergraduate courses in single-variable calculus and an introductory course in probability.
• Hours: 3

• You will discuss operations research problems in seminars. Additionally, you will analyze cases and write reports. If you are a graduate student with a minor or major in operations research, you must attend throughout your entire residence.
• Hours: 1

• Operations Research (OR) involves developing and applying advanced analytical methods to aid complex decisions. Throughout this course, you will learn to apply various analytical methods to diverse applications. These methods include linear and mixed-integer programming, nonlinear and combinatorial optimization, network models, and machine learning. The focus will be on translating real-world problems into models and applying computational procedures and data to aid decision-making. Applications include improving production and service systems, healthcare delivery, and transportation systems. OR also helps make better decisions in sports, marketing, and project management. Prerequisites for this course include undergraduate courses in single-variable calculus and an introductory course in probability.
• Hours: 3

• First, you must complete a master’s thesis, typically involving 3 to 6 credits of OR 695 Master’s Thesis Research. Ideally, your thesis should include publishable research.
• Next, form a Graduate Advisory Committee with at least three faculty members and file a committee-approved Plan of Graduate Work with the Graduate School. Ensure your Chair (or co-chair) and one other member are from the OR Faculty. Additionally, include one member as the Graduate School Representative and one representing your minor field of study.
• Finally, pass your final oral examination conducted by your Advisory Committee. This exam will include, but is not limited to, a “defense of thesis.”
• Once you pass the MSOR final oral examination, ensure each committee member approves your thesis. Submit the thesis to the thesis editor of the Graduate School, adhering to the Guide for Preparation of Theses and Dissertations available from the Graduate School. For detailed information about ETDs, refer to the Electronic Theses and Dissertations page.

OR PRO TIP: Be aware of Graduate School submission deadlines for graduation.

• Hours: 3

OR 505 Linear Programming

• The course covers a wide range of topics. These include an introduction to applications in economics and engineering. It explores methods such as the simplex and interior-point methods. Additionally, it delves into parametric programming and post-optimality analysis. The course also covers duality in matrix games and linear systems solvability theory. Furthermore, it discusses linear systems duality theory and polyhedral sets and cones. This includes their convexity and separation properties, as well as dual representations. Lastly, the course touches upon equilibrium prices, Lagrange multipliers, subgradients, and sensitivity analysis.

OR 506 Algorithmic Methods in Nonlinear Programming

• The course covers a wide range of topics, beginning with an introduction to methods for obtaining approximate solutions to unconstrained and constrained minimization problems of moderate size. Emphasis is placed on the geometrical interpretation and practical application of methods such as coordinate descent, steepest descent, Newton and quasi-Newton methods, conjugate gradient search, gradient projection, and penalty function methods for constrained problems. Specialized problems and algorithms are addressed based on available time.

• Hours: 3

• First, you must complete a master’s thesis, typically involving 3 to 6 credits of OR 695 Master’s Thesis Research. Ideally, your thesis should include publishable research.
• Next, form a Graduate Advisory Committee with at least three faculty members and file a committee-approved Plan of Graduate Work with the Graduate School. Ensure your Chair (or co-chair) and one other member are from the OR Faculty. Additionally, include one member as the Graduate School Representative and one representing your minor field of study.
• Finally, pass your final oral examination conducted by your Advisory Committee. This exam will include, but is not limited to, a “defense of thesis.”
• Once you pass the MSOR final oral examination, ensure each committee member approves your thesis. Submit the thesis to the thesis editor of the Graduate School, adhering to the Guide for Preparation of Theses and Dissertations available from the Graduate School. For detailed information about ETDs, refer to the Electronic Theses and Dissertations page.

OR PRO TIP: Be aware of Graduate School submission deadlines for graduation.

• Hours: 3