Operations Research Implementations
Course Number: 45950
Operations Research Implementations is highly recommended for those students participating in the Business Analytics Track.
Operations research is a key aspect of business analytics. Most real-world operations research projects require data and capabilities beyond what Excel and Solver can offer. Instead, most real implementations are formulated using a special mathematical modeling system (such as OPL, AMPL, MPL, GAMS, or AIMMS), and are solved using a state-of-the-art solver (such as CPLEX, Gurobi, or XPRESS).
The focus of this course is on such professional operations research implementations, where implementation firstly refers to implementing a mathematical model on a computer using a professional optimization system. In addition, the course also discusses potential issues and challenges that are encountered when implementing the outcome of an operations research project in practice.
The course extends known optimization modeling concepts such as variables, objectives and constraints with more abstract modeling concepts such as index sets and parameters, which are indispensable when formulating large-scale optimization models. Furthermore, the course describes how operations research projects can benefit from multiple models that interact to solve the problem. These (and other) topics are combined with hands-on experience with a professional modeling system. The course will include a project to be done in small groups as well as weekly programming assignments.
At the end of this course, you will have learned how large-scale optimization problems (involving hundreds or thousands of variables and constraints) can be solved using a professional optimization system. In particular, you will have experienced the process of operations research implementations through modeling, implementing, solving, and reporting a realistic operations research project. (6/13)
Concentration: Operations Research
Academic Year: 2019-2020
Semester(s): Mini 3