Presented by Professor Joaquim Gromicho (Professor of Business Analytics, University of Amsterdam; Science and Education Officer, ORTEC)
I will tell you some stories that introduce mathematical optimization in python. Each story describes a problem and the solution will be demonstrated using standalone Jupyter notebooks which can be made available on request. The domains addressed include:
Optimization problems with analytical solution
Nonlinear continuous optimization problems
Mixed integer linear optimization problems
Coping with data uncertainty using robust models
Scalable mixed integer convex optimization expressed using second order cones
The illustrations will use python packages that are solver agnostic, meaning that you can easily replace the solver when needed. This can be the case when you start with a free solver but discover that you need a commercial one: replacing the solver will require no recoding of the model.
4 June 2021 webinar presentation relevant information and links
Speaker prof. dr. Joaquim Gromicho is science and education officer at www.ortec.com and professor of Business Analytics at www.uva.nl, see https://abs.uva.nl/content/news/2021/01/improving-the-world-through-analytics.html