Dear all,
The final exam material includes the Lecture slides 1-9 from the E-Class for the Full Course, and the sets 1-6 for the Half Course.
Note that in 9 you should mainly focus on the simple Benders Decomposition approach (not Logic Based Benders) and the Constraint programming c(see up to slide 81 in Lecture 9).
For more details and examples for the material within the Lecture slides you can study the following:
a) Simplex algorithm, Chapters 4-5 of Hillier & Lieberman, “Introduction to Operations Research”,
b) LP Duality Theory, Chapter 6 of Hillier & Lieberman, “Introduction to Operations Research”,
c) Convex sets and functions, Chapters 2-3 of Boyd & Vandenberghe “Convex Optimization”,
d) Descent methods, Chapter 9 of Boyd & Vandenberghe “Convex Optimization”
e) Lagrange duality, Chapter 5 Boyd & Vandenberghe “Convex Optimization”.
f) Interior point methods: Sections 11.1-11.3, Boyd & Vandenberghe, and Lecture notes from the course on Machine Learning by Ryan Tibshirani: https://www.stat.cmu.edu/~ryantibs/convexopt/lectures/barr-method.pdf
g) Integer programming Chapter 11, Hillier & Lieberman, “Introduction to Operations Research”,
h) Branch and Bound, Section 11.6, Hillier & Lieberman, “Introduction to Operations Research”.
i) Benders’ decomposition, in Hooker, J.N. (2019). Logic-Based Benders Decomposition for Large-Scale Optimization. In: Velásquez-Bermúdez, J., Khakifirooz, M., Fathi, M. (eds) Large Scale Optimization in Supply Chains and Smart Manufacturing. Springer Optimization and Its Applications, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-030-22788-3_1 (access with VPN from AUEB)
j) Contstraint programming, Rossi, F., Van Beek, P. and Walsh, T. eds., 2006. “Handbook of constraint programming, Elsevier”
On Monday 16/06, after presenting an application of RL to job shop scheduling, we are going to discuss the solutions of your homework assignment and will answer any questions you may have about the exam material.
Best Regards,
G.
