Nonlinear Programming: Part I

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (30)

Page 3 of 3

Optimization Problems: Standard Form

Explores optimization problems in standard form, convex optimization, and optimality criteria.

Linear Programming: Two-phase Simplex Algorithm

Covers the application of the two-phase Simplex algorithm to solve linear programming problems.

Lagrangian Duality: Convex Optimization

Explores Lagrangian duality in convex optimization, transforming problems into min-max formulations and discussing the significance of dual solutions.

Constrained optimization: the basics

Covers the basics of constrained optimization, including tangent directions, trust-region subproblems, and necessary optimality conditions.

Convex Optimization: Introduction and Sets

Covers the fundamentals of convex optimization, including mathematical problems, minimizers, and solution concepts, with an emphasis on efficient methods and practical applications.

Equivalent formulation

Covers the concept of equivalent formulation in constrained optimization and explores the tangent cone.

Convex Optimization: Dual Cones

Explores dual cones, generalized inequalities, SDP duality, and KKT conditions in convex optimization.

Thermodynamic Properties: Equations and Models

Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.

Hedging for LPs

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

Duality in Linear Programming

Explores the concept of duality in linear programming, discussing the relationship between primal and dual problems.