RESEARCH PAPERS | CONFERENCE PRESENTATIONS | STUDENTS | EDUCATION AND EXPERIENCE |

TEACHING | HONORS AND AWARDS | CV | FUNDING

TEACHING

 

 

IOE310: Introduction to Optimization

This course is about making the best possible decisions in complex and important situations. We will focus on developing mathematical models to represent real-world decisions, and on using algorithms to find optimal solutions to these real-world problems.

Some of the key objectives are to learn:

-- how to formulate models

-- what a linear program(LP)  is

-- how to identify optimal solutions to LP�s graphically

-- what a basic feasible solution is and the link between these solutions and the optimal solution to a problem

-- the simplex method for solving LP�s

-- how to take the dual of an LP

-- the relationship between primal and dual problems in linear programming (complementary slackness) and how this relationship is useful

-- how to analyze the results of a linear program

-- how to modify and re-solve a linear program

-- how to solve an integer program (IP)

-- how to formulate and solve network flow problems

More important than any individual topic or skill, though, is that you learn to think about decision-making systematically. Even though some of you will never again use the optimization tools taught in this class, and others will just �plug and chug� with Excel or some other mainstream software tools, we hope that this course will change the way you view new problems and the way that you organize your thoughts about how to tackle these problems.

 

IOE510: Linear Programming I

Formulation of problems from the private and public sectors using the mathematical model of linear programming. Development of the simplex algorithm; duality theory and economic interpretations. Postoptimality (sensitivity) analysis application and interpretations. Introduction to transportation and assignment problems; special purpose algorithms and advance computational techniques. Students have opportunities to formulate and solve models developed from more complex case studies and to use various computer programs.

 

IOE591: Models and Algorithms for Large-Scale Optimization Problems

Modeling approaches and algorithmic techniques for large-scale optimization problems will be studied through a hands-on, highly-interactive approach centered around collectively solving a challenging real-world problem. Computer exercises, team-work, and class participation will be critical to the course.

 

IOE640: Mathematical Modeling of Operational Systems

The art and science of developing, using and explicating mathematical models, presented in a studio/workshop environment. Structuring of a variety of operational "situations" so they can be reasonably represented by a mathematical model. Extensive class discussion and out-of-class investigation of potential mathematical approaches to each situation. Incorporation of data analysis.