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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.

Complex Systems: Critical Phenomena

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

Duality: Duality in Linear Optimization MOOC: Optimization: principles and algorithms - 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.

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.

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 MOOC: Introduction to Discrete Choice Models

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

The transhipment problem: The shortest path problem MOOC: Optimization: principles and algorithms - Network and discrete optimization

Covers the transhipment and shortest path problems in network optimization.

Metropolis Algorithm: Optimization and Probabilistic Approach

Covers the Metropolis algorithm for approximate optimization using lazy chains and exploring state space efficiently.

Optimization with Constraints: Theory and Applications

Covers the theory and applications of optimization with constraints, including key concepts and numerical methods.

Energy optimization strategies

Covers brainstorming options for smart operation changes, heat recovery, and PV panel performance.

Degree of Freedom Analysis

Explores degree of freedom analysis, redundancy, and data reconciliation in process modeling and optimization.

Combinatorial Optimization: Simulated Annealing

Explores combinatorial optimization using simulated annealing to find ground states in frustrated systems and address challenges in satisfying all interactions simultaneously.