Concept

Combinatorial optimization

Related lectures (30)

Optimization with Constraints: KKT Conditions

Covers the KKT conditions for optimization with constraints, essential for solving constrained optimization problems efficiently.

Energy Systems Optimization

Explores energy systems modeling, optimization, and cost analysis for efficient operations.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Optimization Principles

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

Boolean Algebra: Properties and Optimization

Explores Boolean algebra properties and optimization techniques using Karnaugh diagrams and De Morgan's theorems.

Semi-Definite Programming

Covers semi-definite programming and optimization over positive semidefinite cones.

Complex Systems: Critical Phenomena

Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.

Duality: Duality in Linear Optimization

Covers the concept of linear optimization and the duality relationship between primal and dual problems.

Data reconciliation and parameter identification by FM

Explores measurement analysis, data reconciliation, and parameter identification in energy systems, emphasizing the importance of correct measurements and optimization.

Optimal Decision Making: Exercises and Applications

Covers exercises on optimal decision making, including minimizing costs and optimizing transportation networks.

Introduction to Optimization

Covers the basics of optimization, including historical perspectives, mathematical formulations, and practical applications in decision-making problems.

Optimization with Constraints: KKT Conditions

Covers the optimization with constraints, focusing on the Karush-Kuhn-Tucker (KKT) conditions.

Optimization and Simulation

Explores optimization techniques like Metropolis-Hastings and Simulated Annealing through Markov chains and stationary distributions.

Optimization: Classical Problems

Covers classical optimization problems, brute force algorithms, and integer linear optimization.

ALM with Inequalities: Next Steps in Optimization

Explores the Augmented Lagrangian Method with equality and inequality constraints in optimization, emphasizing the importance of slack variables.

Traveling Salesman Problem: Introduction and Approximation Methods

Introduces the Traveling Salesman Problem and explores approximation methods using Markov chains.

Optimization and Simulation: Heuristics and Neighborhoods

Explores greedy heuristics, neighborhoods in optimization, and local search algorithms.

Optimization and Simulation: Introduction to Simulation

Introduces state-of-the-art methods in optimization and simulation, covering topics like statistical analysis, variance reduction, and simulation projects.

Optimization and Simulation

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

Microeconomic Consumer Theory

Explores microeconomic consumer theory, utility maximization, optimization problems, and decision-making models.