Basic Information Instructor: Dr. Marco A. MONTES DE OCA Office: 315 Ewing Hall Phone: (302) 831-7431 Email: mmontes@math.udel.edu Office hours: Mondays, 5:00pm-7:00pm, or by appointment. Meetings: Mondays and Wednesdays, 3:35pm-4:50pm, 330 Purnell Hall. Syllabus:

Quick Access Slides and Notes Source Code Project Homeworks Exams

Slides and Notes

Session 1: Introduction
Session 2: Optimization via Calculus (Functions of One Variable)
Session 3: Optimization via Calculus (Functions of Several Variables I)
Session 4: Optimization via Calculus (Functions of Several Variables II)
Session 5: Algorithmic Approaches I
Session 6: Algorithmic Approaches II
Session 7: Algorithmic Approaches III
Session 8: Convex Sets and Functions
Session 9: Linear Least Squares
Session 10: Intro to Constrained Optimization: Lagrange Multipliers
Session 11: Constrained Optimization: Bordered Hessian
Session 12: Constrained Optimization: KKT Conditions
Session 13: Constrainted Optimization: Constraint Qualifications
Session 14: Algorithmic Approaches IV: Trust Region Methods
Session 15: Algorithmic Approaches V: Penalty Methods
Session 16: Algorithmic Approaches VI: The Simplex Method for Linear Programming
Session 17: Constrainted Optimization: Duality
Session 18: Constrainted Optimization: Duality, Game Theory and Linear Programming
Session 19: Algorithmic Approaches VII: Derivative-Free, Direct Search, and Heuristic Methods (Particle Swarm Optimization)

Matlab Code

Basic Line Search
Steepest Descent
Newton's Method
Linear Least Squares
Trust Region Method using the Dogleg Technique
Penalty Method for Constrained Optimization (using a trust region method as optimization algorithm)
Augmented Lagrangian Method for Constrained Optimization (using a trust region method as optimization algorithm)
Particle Swarm Optimization

Homeworks

Homework 1		Solution
Homework 2		Solution
Homework 3		Solution
Homework 4		Solution
Homework 5		Solution

Exams

Exam 1
Exam 2