# Operations Research, MSOR

This program seeks to train students in the basic techniques and theory of operations research and their applications to real-world problems. Graduates should have developed their analytical skills to attack complex, large-scale optimization problems of both a deterministic and stochastic nature. Eight 4-semester-hour graduate courses are required for this degree. Previous course work will be evaluated to determine proficiency in certain content areas and degree plan may be tailored accordingly. In some cases, a student may be required to take an assessment exam to determine content and knowledge proficiency. No course can be used to satisfy both a requirement and an elective. To qualify for degree conferral, a minimum cumulative grade-point average of 3.000, equivalent to a grade of B, must be obtained. Some courses listed for this program are offered in the College of Engineering or the College of Computer and Information Systems.

Complete all courses and requirements listed below unless otherwise indicated.

## Core Requirements

Code | Title | Hours |
---|---|---|

Probability | ||

Complete 4 semester hours from the following: | 4 | |

Probability 1 | ||

Probability 2 | ||

Probabilistic Operation Research | ||

Statistics | ||

MATH 7342 | Mathematical Statistics | 4 |

or MATH 7343 | Applied Statistics | |

Operations Research | ||

OR 6205 | Deterministic Operations Research | 4 |

Optimization and Complexity | ||

MATH 7234 | Optimization and Complexity | 4 |

## Approved Electives

Code | Title | Hours |
---|---|---|

Complete 16 semester hours from the following: | 16 | |

Algorithms | ||

Machine Learning | ||

Theory of Computation | ||

Concepts of Object-Oriented Design | ||

Concepts of Object-Oriented Design with C++ | ||

Component Software Development | ||

Pattern Recognition | ||

Combinatorial Optimization | ||

Engineering Project Management | ||

Economic Decision Making | ||

Financial Management for Engineers | ||

Customer-Driven Technical Innovation for Engineers | ||

Product Development for Engineers | ||

Healthcare Systems Modeling and Analysis | ||

Systems Engineering in Public Programs | ||

Lean Concepts and Applications | ||

Mass Customization | ||

Biosensor and Human Behavior Measurement | ||

Manufacturing Methods and Processes | ||

Supply Chain Engineering | ||

Simulation Analysis | ||

Data Mining in Engineering | ||

Statistical Methods in Engineering | ||

Statistical Quality Control | ||

Reliability Analysis and Risk Assessment | ||

Human Factors Engineering | ||

Neural Networks in Engineering | ||

Combinatorial Analysis | ||

Graph Theory | ||

Time Series | ||

Statistical Decision Theory | ||

Stochastic Calculus and Introduction to No-Arbitrage Finance | ||

Inventory Theory | ||

Integer and Nonlinear Optimization | ||

Multi-Criteria Decision Making | ||

Constraint Programming | ||

Logistics, Warehousing, and Scheduling |

## Program Credit/GPA Requirements

32 total semester hours required

Minimum 3.000 GPA required