Optimization: Classical Problems

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Linear Optimization: Fundamentals

Covers the basics of linear optimization, including equations, polyhedrons, feasible directions, and optimal solutions.

Optimization Algorithms

Covers optimization algorithms, convergence properties, and time complexity of sequences and functions.

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Solving Linear Programs: SIMPLEX Method

Explains the SIMPLEX method for solving linear programs and optimizing the solution through basis variable manipulation.

Knapsack Problem: Optimization and Traveling Salesman

Explores the knapsack problem and the traveling salesman problem with a focus on optimization algorithms.

Optimization and Simulation

Explores greedy heuristics in optimization, integrality constraints, and comparison of optimization methods.

Convex Polyhedra and Linear Programs

Explores convex polyhedra, linear programs, and their optimization importance.

Complexity & Induction: Algorithms & Proofs

Covers worst-case complexity, algorithms, and proofs including mathematical induction and recursion.

Branch & Bound: Optimization

Covers the Branch & Bound algorithm for efficient exploration of feasible solutions and discusses LP relaxation, portfolio optimization, Nonlinear Programming, and various optimization problems.

Elements of computational complexity

Covers classical and quantum computational complexity concepts and implications.