Lecture

Extreme Values and Optimization

Related lectures (30)

Optimization with Constraints: KKT Conditions

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

Optimization with Constraints: KKT Conditions

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

Weak and Strong Duality

Covers weak and strong duality in optimization problems, focusing on Lagrange multipliers and KKT conditions.

Energy Systems Optimization

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

Two-Stage Stochastic Programs

Explores Two-Stage Stochastic Programs, problem reformulation, Benders decomposition, extreme points, and sensitivity analysis.

Optimization with Lagrange Multipliers

Covers advanced optimization techniques using Lagrange multipliers to find extrema of functions subject to constraints.

Optimization: Constrained Volume Problems

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

Lagrange Multipliers Theorem

Covers the Lagrange Multipliers Theorem and its applications in finding extrema.

Optimization Methods: Theory Discussion

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

Linear Programming Basics

Covers deriving basic linear program representation, finding solutions, and exploring optimality.

Optimization methods

Covers optimization methods, focusing on gradient methods and line search techniques.

Simplex Algorithm: Basics

Introduces the Simplex algorithm for solving flow problems and handling negative cost cycles.

Gradient Descent: Optimization and Constraints

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

Semi-Definite Programming

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

Introduction to Optimization and Operations Research

Covers fundamental concepts of optimization and operations research, exploring real-world examples and key topics over a semester.

Linear Programming: Weighted Bipartite Matching

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

Optimization Techniques

Covers optimization techniques and their application in solving real-world problems.

Predicting Completion Time: Optimization Strategies

Discusses predicting completion time and optimizing activities through efficient orchestration strategies and experiment-based completion curve predictions.

Degree of Freedom Analysis

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

Rhino to AutoCAD Transition

Explores the transition from Rhino to AutoCAD, focusing on tools and features.