/Numerical-Optimization

This is a course material for numerical optimization to be taught in summer 2020

Primary LanguageJupyter Notebook

Numerical-Optimization

This is a course material for numerical optimization to be taught in summer 2020 (June-August, 10 weeks) through webex. I have not finalized the schedule yet. It is completely open to everyone. If you are interested, please feel free to contact qiang.zhu@unlv.edu between 2020/06-2020/08.

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Textbooks

This course is intended to cover

  • Various optmization methods used in scientific computing
  • Julia programming

The course will mostly follow the book of Algorithms for Optimization by Mykel J. Kochenderfer and Tim A. Wheeler. Here is an intersting video by one of the authors talking about how they wrote the book in a recent Julia confernece.

For some details on the optimization algorithms, we will refer to Numerical Optimization by Jorge Nocedal and Stephen J. Wright

Format

Though this is a virtual class, we plan to make it as interactive as possible. Typically, each class is composed of three units.

  • Codes review (1 or 2 volunteers to review the previous homework assignments)
  • Lecture (Math details for each algorithm)
  • Coding session (code accomplishment of the algos in each lecture)

All codings will be done through jupyter notebook.

Each class will take about 90 minutes.