Optimization covers a broad range of problems that share a common goal - determining the values for the decision variables in a problem that will maximize (or minimize) some objective function while satisfying various constraints. Using a mathematical modeling approach, this course introduces mathematical programming techniques and concepts such as linear programming, sensitivity analysis, network modeling, integer linear programming, goal programming, and multiple criteria optimization. Software is used to solve real-world problems with an emphasis on interpretability of results. Applications include determining product mix, routing and logistics, and financial planning.
- Formulate optimization problems mathematically.
- Solve mathematical programming problems graphically, algebraically, and using software.
- Assess how sensitive models are to various changes that might occur in the model or its optimal solution.
- Identify and apply the most appropriate mathematical programming technique for problem solution.
- Interpret and understand the computer output for a mathematical programming application.
- Document and articulate the results and conclusions for mathematical programming techniques applied to actual cases in a variety of disciplines.