Lectures related to Constraint (mathematics)

Optimization with Constraints: KKT Conditions

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

Constraints and Lagrange

Introduces constraints, Lagrange multipliers, and generalized coordinates in physics.

Optimization with Constraints: KKT Conditions Explained

Covers the KKT conditions for optimization with constraints, detailing their application and significance in solving constrained problems.

Optimization with Constraints: KKT Conditions

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

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.

Optimization: Constrained Volume Problems

Explores constrained volume problems using Lagrange multipliers to find extrema under constraints in various examples.

Optimization in Energy Systems

Explores optimization in energy systems, focusing on decision-making through objective functions and constraints to determine system states.

Automated Planning: Modeling and Constraints

Explores automated planning, constraints, and applications in diverse domains, emphasizing the challenges and efficiency of solving planning problems.

Formulation, Problem Transformations

Explores transforming optimization problems to meet algorithm requirements and make them equivalent.

Linear Optimization Techniques: Problem Solving Approaches

Provides an overview of linear optimization techniques, focusing on problem-solving methods and the importance of constraints and objective functions.

Optimization with Inequalities

Explores optimization with inequality constraints, emphasizing finding extreme values and stationary points.

Extremum of a Function: Constraints

Explores extremum of a function under constraints and finding candidate points in practice.

Linear Programming: Optimization and Duality

Introduces linear programming, optimization, and duality concepts with a focus on the simplex method and practical examples.

Equality and Inequality Constraints: Optimization Conditions

Covers necessary optimality conditions for optimization with constraints and discusses cones and polar sets.

Linear constraints: Standard form

Covers linear constraints in standard form, including equality constraints, rank, and redundant constraints.

Simplex Algorithm: Initial Tableau, Simple Case

Covers the simplex algorithm applied to the simple case of inequality constraints.

Hedging for LPs

Covers the concept of hedging for Linear Programs and the simplex method, focusing on minimizing costs and finding optimal solutions.

Optimization Framework: Inequality Constraints

Covers an optimization framework with inequality constraints and Karush-Kahn Tucker conditions.

Calculus of Variation and Euler's Elastica

Covers variational methods, equilibrium shape of a bent beam, Euler's Elastica, and numerical and analytical methods.

Optimization in Engineering

Explores optimization methods in engineering, covering decision variables, constraints, and various solving techniques.