Outline
First Day: Introduction
0. Outline of the course
Part I: Optimization models
1. Optimization concepts
2. Computational methods for optimization
3. Advanced topics in optimization
4. Practice session 1
Part II: Dynamic models
5. Dynamical systems and analysis
6. Practice session 2
7. Simulation methods
8. Practice session 3
Part III: Probability models
9. Probability and stochastic processes
10. Practice session 4
11. Monte Carlo simulation
12. Practice session 5
Review Sessions
13. Review session (by appointment)
Schedule
Part I (Prof. Maeda)
Sessions 0-1: April 10, 2024; Lecture in person*
Session 2: April 17, 2024; Lecture in person* + Computer work and self-study
Session 3: April 24, 2024; Lecture in person*
Session 4: May 1, 2024; Computer work and self-study (no class)
Part II (Prof. Kansha)
Session 5: May 8, 2024; Lecture in person*
Session 6: May 22, 2024; Computer work and self-study (no class)
Session 7: May 29, 2024; Lecture in person*
Session 8: June 5, 2024; Computer work and self-study (no class)
Part III (Prof. Narita)
Session 9: June 12, 2024; Lecture in person*
Session 10: June 19, 2024; Computer work and self-study (no class)
Session 11: June 26, 2024; Lecture in person*
Session 12: July 3, 2024; Computer work and self-study (no class)
(Session 13: July 10, 2024; Review by appointment)
* Class format is subject to change.