Dual M.S. in Industrial Engineering and Operations Research

The dual-title degree in Operations Research is offered as an option through graduate programs in eight colleges. The program enables students to attain and be identified with the tools, techniques, and methodology of operations research while maintaining a close association with industrial engineering. Operations research is the analysis—usually involving mathematical treatment—of a process, problem, or operation to determine its purpose and effectiveness and to gain maximum efficiency.

Admission Requirements 

A student must first be admitted to one of the Industrial Engineering M.S. tracks. 

For the M.S. dual-title degree in Operations Research, prerequisites for acceptance to the program without deficiency include the following or their equivalent: MATH 140, MATH 141, MATH 220; CMPSC 101; and 3 credits of Probability and Statistics. These are in addition to those prescribed by the graduate major program. The application for admission to the dual masters degree must be submitted at least one semester before the student intends to graduate.

Dual M.S. Requirements

If a thesis is required, the adviser must be a member of the graduate faculty recommended by the chair of the industrial engineering program and a member of the Operations Research faculty. The reader of the thesis must be from outside the industrial and manufacturing engineering department and a member of the Operations Research faculty. A paper or report may be written in lieu of the M.S. thesis upon approval of the Industrial Engineering program. The adviser must be a member of the graduate faculty recommended by the head of the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering and a member of the Operations Research faculty. The reader of the paper must be from outside of the Industrial Engineering program and a member of the Operations Research faculty.

Note: All course descriptions can be found in LionPATH.

Stochastic/Statistical Methods - 6 credits

Stochastic Processes - minimum of 3 credits

  • IE 516/SCIS 516: Applied Stochastic Processes
  • MATH 416/STAT 416: Stochastic Modeling, or MATH 516: Stochastic Processes, or MATH 519/STAT 519: Topics in Stochastic Processes
  • STAT 515: Stochastic Processes and Monte Carlo Methods

Statistical Methods - minimum of 3 credits

  • MATH 414/STAT 414: Introduction to Probability Theory, or MATH 415/STAT 415: Introduction to Mathematical Statistics, or MATH 418/STAT 418: Introduction to Probability and Stochastic Processes for Engineering
  • IE 511: Experimental Design in Engineering, or IE 583: Response Surface Methodology and Process Optimization, or IE 584: Time Series Control and Process Optimization
  • SC&IS 535: Statistical Research Methods for Supply Chain and Information Systems
  • STAT 460: Intermediate Applied Statistics, or STAT 501: Regression Methods, or STAT 502: Analysis of Variance and Design of Experiments, or STAT 503: Design of Experiments
  • ECON 501: Econometrics
  • AEREC 510/ECON 510: Econometrics I

Optimization - 6 credits

Linear Programming - minimum of 3 credits

  • IE 405: Deterministic Models in Operations Research or MATH 484: Linear Programs and Related Problems
  • IE 505: Linear Programming
  • AEREC 527: Quantitative Methods I

Integer Programming

  • IE 510: Integer Programming

Mathematical Programming

  • MATH 555/CSE 555: Numerical Optimization Techniques
  • IE 468: Optimization Modeling and Methods, or IE 512: Graph Theory and Networks in Management, or IE 520: Multiple Criteria Optimization
  • SCIS 525: Supply Chain Optimization

Nonlinear Programming

  • IE 521: Nonlinear Programming

Dynamic Programming

  • IE 519/SCIS 519: Dynamic Programming

Computational Methods - 3 credits

Numerical Methods

  • MATH 451/CMPSC 451: Numerical Computations, or MATH 455/CMPSC 455: Introduction to Numerical Analysis I, or MATH 456/CMPSC 456: Introduction to Numerical Analysis II, or MATH 550/CSE 550: Numerical Solution of Ordinary Differential Equations, or MATH 553/CSE 553: Introduction to Approximation Theory

Simulation Methods

  • IE 453: Simulation Modeling for Decision Support
  • IE 522: Discrete Event Systems or I E 540: Manufacturing Systems Siumulation
  • SCIS 545: Supply Chain Simulation

Applications/Specializations - 3 credits

Includes courses in the above areas as well as courses in quality control, scheduling, inventory, queuing, decision analysis, game theory, logistics, expert systems, econometrics, forecasting, and others. Some graduate level courses in this group are: ABE 559; CSE 565, CSE 560, CSE 555, CSE 563, CSE 564; ECON 521; EE 529, EE 581; GEOG 425, GEOG 455, GEOG 481, GEOG 580, GEOG 581; IE 402, IE 425, IE 454, IE 507, IE 509, IE 532, IE 554, IE 562, IE 566; MATH 485, MATH 486; MKTG 511, MKTG 555; PNG 512, P N G 514; STAT 510, STAT 540; SCIS 505, SCIS 510, SCIS 520, SCIS 530.

Operation Research Colloquium

Students must take one credit of OR 590: Operations Research Colloquium, for each year the student takes to complete his/her masters degree. The maximum number of required credits of OR 590 for a dual master's degree is 2.

For additional information, please visit the Operations Research program website.

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Home of the first established industrial engineering program in the world, the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering (IME) at Penn State has made a name for itself in the engineering industry through its storied tradition of unparalleled excellence and innovation in research, education, and outreach.

We are Innovators. We are Makers. We are Excellence in Engineering. We are Penn State IME.

The Harold and Inge Marcus Department of
Industrial and Manufacturing Engineering

310 Leonhard Building

The Pennsylvania State University

University Park, PA 16802-4400

Phone: 814-865-7601

FAX: 814-863-4745