Curriculum | MOR | MSOR

• Seminar discussion of operations research problems. Case analyses and reports. Graduate students with minors or majors in operations research are expected to attend throughout the period of their residence.
• Hours: 1

• Operations Research (OR) is a discipline that involves the development and application of advanced analytical methods to aid complex decisions. This course will provide students with the skills to be able to apply a variety of analytical methods to a diverse set of applications. Methods considered include linear and mixed-integer programming, nonlinear and combinatorial optimization, network models, and machine learning. Focus will be on how to translate real-world problems into appropriate models and then how to apply computational procedures and data so that the models can be used as aids in making decisions. Applications will include improving the operation of a variety of different production and service systems, including healthcare delivery and transportation systems, and also how OR can be used to make better decisions in areas like sports, marketing, and project management. Prerequisites include undergraduate courses in single variable differential and integral calculus and an introductory course in probability.
• Hours: 3

• Seminar discussion of operations research problems. Case analyses and reports. Graduate students with minors or majors in operations research are expected to attend throughout the period of their residence.
• Hours: 1

• Operations Research (OR) is a discipline that involves the development and application of advanced analytical methods to aid complex decisions. This course will provide students with the skills to be able to apply a variety of analytical methods to a diverse set of applications. Methods considered include linear and mixed-integer programming, nonlinear and combinatorial optimization, network models, and machine learning. Focus will be on how to translate real-world problems into appropriate models and then how to apply computational procedures and data so that the models can be used as aids in making decisions. Applications will include improving the operation of a variety of different production and service systems, including healthcare delivery and transportation systems, and also how OR can be used to make better decisions in areas like sports, marketing, and project management. Prerequisites include undergraduate courses in single variable differential and integral calculus and an introductory course in probability.
• Hours: 3

• You must successfully complete a master’s thesis (3 to 6 credits of OR 695 Master’s Thesis Research). Ideally, your thesis will be of sufficient caliber to include publishable research.
• Next, form a Graduate Advisory Committee, consisting of at least three faculty, and file a committee-approved Plan of Graduate Work with the Graduate School. Your Chair (or co-chair) and one other committee member should be a member of the OR Faculty. One committee member must serve as the Graduate School Representative. At least one member should represent your minor field of study.
• Finally, you must pass your final oral examination conducted by your Advisory Committee. At the committee’s discretion, the exam will include but need not be restricted to a “defense of thesis.”
• Upon passing the MSOR final oral examination, you must have the thesis approved by each member of your advisory committee. The thesis must be submitted to the thesis editor of the Graduate School and must conform to the Guide for Preparation of Theses and Dissertations. You can get a copy from the Graduate School. You can find detailed information regarding ETD’s on the Electronic Theses and Dissertations page.

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

• Hours: 3

OR 505 Linear Programming

• Introduction including applications to economics and engineering; the simplex and interior-point methods; parametric programming and post-optimality analysis; duality matrix games, linear systems solvability theory and linear systems duality theory; polyhedral sets and cones, including their convexity and separation properties and dual representations; equilibrium prices, Lagrange multipliers, subgradients, and sensitivity analysis.

OR 506 Algorithmic Methods in Nonlinear Programming

• Introduction to methods for obtaining approximate solutions to unconstrained and constrained minimization problems of moderate size. Emphasis on geometrical interpretation and actual 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 treated as time permits.

• Hours: 3

• You must successfully complete a master’s thesis (3 to 6 credits of OR 695 Master’s Thesis Research). Ideally, your thesis will be of sufficient caliber to include publishable research.
• Next, form a Graduate Advisory Committee, consisting of at least three faculty, and file a committee-approved Plan of Graduate Work with the Graduate School. Your Chair (or co-chair) and one other committee member should be a member of the OR Faculty. One committee member must serve as the Graduate School Representative. At least one member should represent your minor field of study.
• Finally, you must pass your final oral examination conducted by your Advisory Committee. At the committee’s discretion, the exam will include but need not be restricted to a “defense of thesis.”
• Upon passing the MSOR final oral examination, you must have the thesis approved by each member of your advisory committee. The thesis must be submitted to the thesis editor of the Graduate School and must conform to the Guide for Preparation of Theses and Dissertations. You can get a copy from the Graduate School. You can find detailed information regarding ETD’s on the Electronic Theses and Dissertations page.

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

• Hours: 3