Formulation, Problem Transformations

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (32)

Page 1 of 4

Optimization with Constraints: KKT Conditions

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

Optimization Methods: Theory Discussion

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

Gradient Descent: Optimization and Constraints

Discusses gradient descent for optimization with equality constraints and iterative convergence criteria.

Linear Programming: Weighted Bipartite Matching

Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.

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 Principles

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

Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.

Linear Optimization: Fundamentals

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

Semi-Definite Programming

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