Masters in Operations Research

Master of Science
Classroom, Online, Off-site
Main Campus - Melbourne, Virtual Site, Aberdeen
Major Code: 8074 Degree Awarded: Master of Science
Age Restriction: N Admission status: graduate, online graduate main campus, Extended Studies
Delivery Mode/s: classroom, online
Admission Materials: none Location/s: main campus, Aberdeen, Virtual Site

Operations research is a scientific approach to analyzing problems and making decisions. It uses mathematics and mathematical and computational modeling to forecast the implications of various choices and identify the best alternatives.

Operations research techniques are applied to a broad range of problems in both the public and private sectors. These problems often involve designing systems to operate in the most effective way. Many problems deal with the allocation of scarce human resources, money, materials, equipment or facilities. Applications include staff scheduling, vehicle routing, warehouse location, product distribution, quality control, traffic light phasing, police patrolling, preventive maintenance scheduling, economic forecasting, design of experiments, power plant fuel allocation, stock portfolio optimization, cost-effective environmental protection, inventory control and university course scheduling.

Operations research is interdisciplinary and draws heavily from the mathematics program. It also uses courses from computer science, systems engineering and other engineering programs.

The Master of Science in Operations Research offers concentrations that emphasize those areas of application most in demand in today's job market. Graduates have skills that include probability and statistics, deterministic and stochastic models, optimization methods, computation and simulation, decision analysis and the ability to effectively communicate with clients and managers. In addition, graduates have a breadth of knowledge that allows them to work in teams, interacting with people who bring different expertise to a problem. All areas involve expertise with standard computer software packages.

Admission Requirements

An applicant for the master's program in operations research should have an undergraduate major in a science or engineering discipline that requires a significant amount of mathematics. Business majors with strong quantitative backgrounds are also encouraged to apply. A proficiency in mathematics covering topics in calculus, probability theory, statistics, linear algebra, and computer literacy must be demonstrated by testing or suitable coursework.

General admission requirements and the process for applying are presented in the Academic Overview section.

Degree Requirements

The master of science degree can be pursued with either a thesis or nonthesis option; each requires 30 credit hours. Under the thesis option, up to six credit hours of thesis may be granted in place of electives toward the required 30 credit hours and an oral defense is required. The nonthesis option requires a final program examination. Courses taken to satisfy admission prerequisites cannot be counted toward the degree requirements.


The program's curriculum is designed to provide breadth with some flexibility to accommodate the diversity of backgrounds typically found in an operations research program. Greater flexibility is provided for the elective courses beyond the core. A student has the choice of developing greater depth in one area of specialization, aiming at eventual research in that area, or continuing to develop breadth across more than one area. By choosing courses in a related field of application, students can prepare for careers in specialty areas such as management science, actuarial science or economic modeling in addition to conventional areas of operations research.

Each student will complete a program plan that satisfies the requirements listed below, subject to approval of the department head. Substitutions are sometimes permitted.

Core Courses (12 credit hours)
  • MTH 5411 Mathematical Statistics 1
    Credit Hours: 3
    Covers discrete and continuous random variables, generating and moment generating functions, multivariate distributions, covariance and correlation, sums of independent random variables, conditional expectation, Central Limit Theorem, Markov and Chebyshev inequalities and the Law of Large Numbers.
  • ORP 5001 Deterministic Operations Research Models
    Credit Hours: 3
    An applied treatment of modeling, analysis and solution of deterministic operations research problems. Includes model formulation, linear programming, network flow and transportation problems and algorithms, integer programming and dynamic programming.
  • ORP 5002 Stochastic Operations Research Models
    Credit Hours: 3
    An applied treatment of modeling, analysis and solution of probabilistic operations research problems. Topics chosen from decision analysis, game theory, inventory models, Markov chains, queuing theory, simulation, forecasting models.
Select one course:
  • ORP 5003 Operations Research Practice
    Credit Hours: 3
    Includes OR methodology, how an OR analyst interacts with clients, and preparation and presentation of oral reports. Students form teams to analyze real cases where each student gets an opportunity to be a team leader and present oral reports.
  • ORP 5010 Mathematical Programming
    Credit Hours: 3
    Surveys popular optimization techniques. Topics chosen from linear, integer, nonlinear, dynamic and network flow programming; combinatorial graph algorithms.
    Prerequisite course or instructor approval
Restricted Electives (9 credit hours from the following)
  • MTH 5051 Applied Discrete Mathematics
    Credit Hours: 3
    Logic fundamentals, induction, recursion, combinatorial mathematics, discrete probability, graph theory fundamentals, trees, connectivity and traversability. Applications from several fields of science and engineering, including computer science, operations research, and computer and electrical engineering.
  • MTH 5102 Linear Algebra
    Credit Hours: 3
    Linear algebra, systems of linear equations and Gauss elimination method; inverses, rank and determinants; vector spaces; linear transformations, linear functional and dual spaces; eigenvalues, eigenvectors; symmetric, Hermitian and normal transformations; and quadratic forms.
  • MTH 5401 Applied Statistical Analysis
    Credit Hours: 3
    Covers statistical distributions, statistical tests for data, least squares and regression, estimations, tests of hypotheses, analysis of variance, planning and designing research experiments, randomized blocks, Latin and Graeco-Latin squares and data reduction, analysis using ANOVA (analysis of variance) and other methods.
  • MTH 5412 Mathematical Statistics 2
    Credit Hours: 3
    Includes maximum likelihood and Bayes estimators, confidence intervals, testing hypotheses, uniformly most powerful tests, nonparametric methods (chi-square and Kolmogorov-Smirnov goodness-of-fit tests) and regression analysis.
  • ORP 5020 Theory of Stochastic Processes
    Credit Hours: 3
    Introduces stochastic models, discrete- and continuous-time stochastic processes, point and counting processes, Poisson counting process, compound Poisson processes, nonstationary Poisson processes, renewal theory, regenerative processes and Markov chains.
    Prerequisite course or instructor approval
  • ORP 5021 Queuing Theory
    Credit Hours: 3
    Includes queuing processes; imbedded and continuous time parameter processes; Markov, semi-Markov and semi-regenerative processes; single-server and multiserver queues; processes of servicing unreliable machines and computer applications; and controlled stochastic models.
    Prerequisite course or instructor approval
Computation Elective (3 credit hours from the following)
  • MTH 5301 Numerical Analysis
    Credit Hours: 3
    Includes Gaussian elimination and solution of linear systems of equations, root finding methods, systems of nonlinear equations, interpolation, numerical integration, initial value problems for ODEs and fast Fourier transform.
  • MTH 5320 Neural Networks
    Credit Hours: 3
    Introduces architectures, algorithms and applications. Includes single and multilayer perceptrons, counterpropagation, Kohonen self-organization, adaptive resonance theory, neocognition, probabilistic neural networks and Boltzmann machines with and without learning, recurrent neural networks.
  • ORP 5050 Discrete System Simulation
    Credit Hours: 3
    Covers the principles of building and using a discrete event simulation; construction and statistical testing of random variate generators; statistical analysis and validation of results; design of simulation projects; and variance reduction methods.
    Instructor approval or prerequisite course
Free Electives (6 credit hours)
Nonthesis option:

Three courses in areas of interest to the student as approved in the student's program plan.

Thesis option:

At least one course plus up to six credit hours for a thesis. The thesis should be an in-depth study of some topic and/or problem in operations research, subject to the approval of the thesis committee.