divergence

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: Download paper

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  1. Slides and Notes
  2. Source Code
  3. Project
  4. Homeworks
  5. Exams

 

 

 

Slides and Notes

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

Matlab Code

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

Homeworks

Homework 1 Download paper Solution Download paper
Homework 2 Download paper Solution Download paper
Homework 3 Download paper Solution Download paper
Homework 4 Download paper Solution Download paper
Homework 5 Download paper Solution Download paper

Exams

Exam 1 Download paper
Exam 2 Download paper