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

Probability
Complete 4 semester hours from the following: 4
Probability 1
Probability 2
Probabilistic Operation Research
Statistics
MATH 7342Mathematical Statistics4
or MATH 7343 Applied Statistics
Operations Research
OR 6205Deterministic Operations Research4
Optimization and Complexity
MATH 7234Optimization and Complexity4

Approved Electives

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