Dual Ph.D. in Industrial Engineering and Operations Research

The Operations Research dual-title degree 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 the Industrial Engineering Ph.D. program

For the Ph.D. dual-title degree in Operations Research, prerequisites for acceptance to the program without deficiency include the following or their equivalent: MATH 401, MATH 436; 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 doctoral degree must be submitted before the student takes the candidacy examination.

Note: All course descriptions can be found in LionPATH.

Degree Requirements

To qualify for a dual-title degree, students must satisfy the requirements of the Ph.D. in Industrial Engineering, in addition to the minimum requirements, or their equivalent, in the Operations Research program.

The doctoral committee for a Ph.D. dual-title degree student is recommended by the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering. The chair and at least two members of a doctoral committee must be members of the Operations Research faculty. Operations Research must be integrated into the student's candidacy examination. The doctoral committee for a student seeking a minor in Operations Research must have at least one member from the Operations Research faculty.

Note: All course descriptions can be found in LionPATH.

Stochastic/Statistical Methods - 9 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
  • SCIS 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 - 9 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/SC&IS 519: Dynamic Programming

Computational Methods - 6 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 - minimum of 3 credits

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

Applications/Specializations - 12 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, PNG 514; STAT 510, STAT 540; SCIS 505, SCIS 510, SCIS 520, SCIS 530.

Operations Research Colloquium

Students must take one credit of OR 590: Operations Research Colloquium, for each year the student takes to complete his/her doctoral degree. The maximum number of required credits of OR 590 for a dual Ph.D. degree is 4.

Note: A minimum of 18 credits must be in the 500 series, and particular courses may satisfy both the graduate major program requirements and those in the Operations Research program.

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