Course Announcement - Spring 2017

Math 170: Introduction to Optimization

Instructor: Bernd Sturmfels

Office hours: Mondays 3-4:30pm and Thursdays 8-9:30am
Contact: bernd at math, 925 Evans, phone messages: 642 6550

External consultant: Joe Kileel
Office hours on two Tuesdays: March 14 and 21, 1-2:30pm, in 775 Evans
Internal consultant: Julio Soldevilla
Office hours on two Wednesdays: March 15 and 22, 2:30-4:00pm, in 925 Evans

Lectures: Tuesdays and Thursdays 9:30-11:00, 3107 Etcheverry Hall

First Day of Class: Tuesday, January 17
Last Day of Class: Thursday, April 27
Midterm Exam: Thursday, March 2
Term Papers Due: Thursday, May 11

Prerequisites: Linear Algebra (Math 110)
Basics of mathematical software (e.g. SAGE, Maple, or Mathematica)
To brush up on MATLAB, consider enrolling in Math 98 this semester.

Course text: Introduction to Linear Optimization
by Dimitris Bertsimas and John N. Tsitsiklis, Athena Scientific 1997.

Syllabus: We plan to study topics from the following chapters in the text book:
1. Introduction
2. Geometry of Linear Programming
3. The Simplex Method
4. Duality Theory
5. Sensitivity Analysis
7. Complexity and the Ellipsoid Method
8. Interior Point Methods
10-11. Integer Programming
We end with a brief introduction to Semidefinite Programming

The sections to be covered in each lecture are listed below. Please read these before coming to class.

Grading: There will be weekly homework sets and a midterm exam (in-class). The midterm covers Chapters 1,2,3,4.
The final is a term paper (take-home). The grading scheme is: Homework 35%, Midterm 30%, Term Paper 35%.

Homework: There will be a weekly homework assignment, to be handed in on Tuesdays at 11:00am, at the end of class.
Late homework will not be accepted. No exceptions. The assignments, posted below, refer to the text book.
No homework after spring break, so you can focus on your term paper.

Midterm Exam: The midterm covers the first four chapters and is held in class on Thursday, March 2.
This is an open book exam. The exam and solutions are posted here.

Final Exam: You will write a term paper on a topic of their choice related to the class. This can focus on foundational
mathematics (e.g. geometry and combinatorics of convex sets), or involve computing and software, or develop an
application of optimization that interests you. Your choice. You may work on this by yourself or in teams of two.
Please submit a proposal for your project by Thursday, March 23. This should fit on one page and contain:
names of author(s), title, sources, and a brief description. The final version of the paper is due on Thursday, May 11.

Student Presentations: Short talks on the term papers are scheduled for April 24,25,26,27.
Click here for the schedule. Registered students are expected to attend all lectures.

DAILY SCHEDULE:
Jan 17: 1.1 Variants, 1.2 Examples, 1.3 Piecewise linear convex objective functions
Jan 19: 1.4 Graphical solution, 2.1 Polyhedra and convex sets
Jan 24: 2.2 Vertices, 2.3 Standard form, 2.4 Degeneracy
Jan 26: 2.5-2.6 Existence and optimality of extreme points,2.7 Bounded polyhedra
Jan 31: 2.8 Fourier-Motzkin elimination, 3.1 Optimality conditions
Feb 2: 3.2-3.3 Simplex method
Feb 7: 3.4 Anticycling, 3.5 Phase One, 3.6 Column Geometry
Feb 9: Mathematical Software for Optimization
Feb 14: 3.7 Computational Efficiency, 4.1 Motivation for Duality
Feb 16: 4.2 Dual problem, 4.3 Duality theorem
Feb 21: 4.4 Marginal cost, 4.5 Dual simplex method
Feb 23: 4.6 Farkas Lemma, 4.7 Separating hyperplanes, 4.8 Cones
Feb 28: 4.9 Representation of polyhedra, Review
Mar 2: MIDTERM EXAM
Mar 7: 5.2 Global dependence on right-hand side, 5.3 Set of dual optimal solutions
Mar 9: 5.4 Global dependence on cost, 5.5 Parametric programming
Mar 14: 10.1 Modeling techniques, 10.2 Guidelines for strong formulations
Mar 16: 10.3 Modeling with exponentially many constraints, 11.1 Cutting plane methods
Mar 21: 11.2 Branch and bound, 11.3 Dynamic programming
Mar 23: 11.4 Integer programming duality
Apr 4: Interior point methods
Apr 6: Semidefinite programming
Apr 11: Polynomial optimization via sums of squares
Apr 13: No class: work on term paper
Apr 18: No class: work on term paper
Apr 20: No class: work on term paper
Apr 24, Mon 5-7pm (939 Evans Hall): Student presentations
Apr 25, Tue 9:30-11am (3107 Etcheverry): Student presentations
Apr 26, Wed 5-7pm (939 Evans Hall): Student presentations
Apr 27, Thu 9:30-11am (3107 Etcheverry): Student presentations

Homework assignments:
due Jan 24: (Section 1.7) Exercises 1.1, 1.4, 1.7, 1.8, 1.12, 1.14, 1.19
due Jan 31: (Section 2.10) Exercises 2.1, 2.3, 2.4, 2.6, 2.7, 2.9, 2.10
due Feb 7: (Sections 2.10 and 3.9) Exercises 2.18, 2.21, 2.22, 3.2, 3.3, 3.5, 3.6, 3.10
due Feb 14: (Section 3.9) Exercises 3.16, 3.17, 3.19, 3.20, 3.22, 3.26, 3.28, 3.29, 3.30
due Feb 21: (Section 4.12) Exercises 4.1, 4.2, 4.4, 4.5, 4.6, 4.12, 4.13, 4.16
due Feb 28: (Section 4.12) Exercises 4.21, 4.24, 4.25, 4.29, 4.30, 4.31, 4.35, 4.36, 4.39
due Mar 14: (Section 5.7) Exercises 5.3, 5.8, 5.10, 5.11, 5.13, 5.15
due Mar 21: (Sections 10.5 and 11.10) Exercises 10.1, 10.5, 10.10, 10.12, 10.14, 11.1, 11.2, 11.3