Table of contents
Description
This course deals with one specific mathematical model: the linear programming model. This model has a wide range of practical applications, and is of interest to practitioners in operations research, statistics, economics, management and psychology. This, and the fact that good algorithms can solve huge linear programs, is reason for the considerable succes of this model. The theory of the course treats the simplex algorithm, duality theory, and sensitivity analysis. Many examples from practice illustrate the power of the model and teach the student the skill of modelling. Computer sessions teach the student how to solve linear programs with Matlab.
Knowledge and understanding
Knowledge of the existing algorithms for linear programming.
Knowledge of the areas of application. Insight into duality theory, dual variables, sensitivity analysis.
The use of knowledge and insight: Formulate a practical problem as a linear programming problem, solve it with appropriate software, and interpret the results.
Making Judgements
Recognize when a problem is a linear programming problem.
Recognize sensitive data.
Communication
Communicate the results of software. Communicate why a chosen linear programming formulation correctly models a given problem.
Skills
Solve a small linear program by hand. Interpret and manipulate simplex tableaus.
Formulate a problem as a linear programming problem. Write and interpret dual linear programs. Perform an optimality check on a given solution. Perform sensitivity analysis.
Comments
http://www2.ohlone.edu/people2/joconnell/ti/simplex8384.pdf