In the first week, we will have a look at different types of optimization problems and see some Python code at work. We will encounter the definition of convexity (for sets and functions) and identify some problems as convex. After a brief overview of the computational environment, we will get started with the topic of unconstrained optimization and (if time permits) discover a first minimization algorithm.

Learning outcomes

  • Know examples of different types of optimization problems.
  • Have a vague idea of how to use Python.
  • Know the definition convexity, examples of convex functions, and its significance for optimization.

Tasks and Materials

  • Browse through the Preliminaries – don’t worry if you are not familiar with everything in there, the more advanced concepts will be introduced as needed.
  • The lecture notes are available here.
  • The first problem sheet will be available in Week 2. The problem class in week 1 will be used to review background material and as an introduction to Python.