Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Covers the Simplex algorithm for function minimization with linear constraints.
Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.
Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.
