Optimal Decision Making: Exercises and Applications

Related lectures (31)

Page 3 of 4

Covers energy system modelling, optimization, scenarios, predictions, complexities, and controversies in energy models.

Covers dynamic programming with a focus on Fibonacci numbers and efficient calculation algorithms.

Introduces convex optimization, covering convex sets, solution concepts, and efficient numerical methods in mathematical optimization.

Covers the basics of the Simplex method and its application in solving optimization problems.

Explores the dual formulation of Support Vector Machines for hard margin classification.

Covers optimization principles, including linear optimization, networks, and concrete research examples in transportation.

Covers optimization problems, minimal packing, and bounds in Integer Optimization.

Explores optimization problems solved with greedy algorithms and proves the optimality of the Cashier's Algorithm for U.S. coins.

Covers exercises on convex optimization, focusing on formulating and solving optimization problems using YALMIP and solvers like GUROBI and MOSEK.

Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.