Optimization methods for agriculture insurance
Project scope
Categories
DatabasesSkills
computer simulation python (programming language) mathematical modeling agricultureThis project is an application of mathematical modelling and optimization to a livestock insurance problem. The goal is to analyze various scenarios from a farmer’s perspective and to minimize the loss. The main idea is to design and implement in Python a numerical simulation, including various scenarios in terms of the farm size and insurance premiums.
The student will:
-find a mathematical model for livestock agriculture insurance problems
-apply an appropriate optimization method depending on the farm size and insurance premiums to minimize farmers' loss
-write Python code to implement numerical simulations for various scenarios
- interpret the results and write a final report
I will supervise and support the student to complete the project. I plan to have weekly or biweekly meeting to discuss the training needed and the progress of the project. I will
guide the student to study several optimizations methods and choose the most appropriate one for the project. We will work together on the mathematical modelling part and to
design the algorithms for the numerical simulations.
About the company
The Department of Mathematics and Statistics provides a vibrant and supportive home base for students who want to study mathematics and statistics. Our growing department is home to excellent scholars and has a deep commitment to student success, whether taking math as a requirement or as a pursuit of passion. Our faculty members are dedicated to providing an education that emphasizes the knowledge and broad analytical skills that are valuable in today’s world.
Beyond the classroom, our department organizes Torus Talks, a regular presentation series where faculty and students share insights into the uses and versatility of mathematics and statistics, and a Math Help Centre, where students can access additional support in mastering their course work.
Portals
