Download the full Syllabus.
Course description: There are many solutions to a given problem, but selecting the solution with the lowest annual cost would be the most desirable one. Modeling, linear programming and search optimization techniques along with spreadsheets allow us to examine alternative solutions for a problem. This course will introduce the key ideas of modeling and optimization of systems, and methods of management decision-making using Solver™ and MS-Excel™.
Course Learning Objectives: Upon completion of this course, the students should be able to:
- Identify the systems related to food and agricultural systems.
- Construct a model by studying the environment and identifying the inputs, processes and outputs of a system.
- Learn and apply the optimization methods to various problems in food and agricultural systems.
- Develop models and apply linear, integer and nonlinear optimization techniques to generate solutions.
- Use Solver™, MS-Excel™ and software tools for linear and non-linear optimization.
- Understand and interpret the results of the solutions.
Tentative lecture schedule:
| Week | Topics | Assignment |
| Week 1 | Course overview, concept and definition of terms | |
| Week 2 | Excel spreadsheet introduction
Calculation and modeling with Excel |
|
| Week 3 | Linear Programming – Model development | |
| Week 4 | Linear Programming – Graphical solution | |
| Week 5 | Linear Programming – Computer solution | Exam 1 |
| Week 6 | LP output interpretation
LP Applications |
|
| Week 7 | LP Applications | |
| Week 8 | LP network models | |
| Week 9 | Distribution and network models | Exam 2 |
| Spring Break | ||
| Week 11 | Integer LP | |
| Week 12 | Integer LP | |
| Week 13 | Non-linear programming | |
| Week 14 | Block chain and IoT in management | |
| Week 15 | Project scheduling; course project presentation | |
| Week 16 | Course project presentation | Exam 3 |
| Finals | No class | |
Note: Schedule is subject to change