STAT 28000. Optimization

Department of Statistics
University of Chicago
Spring 2016

This is an introductory course on optimization that will cover the rudiments of unconstrained and constrained optimization of a real-valued multivariate function. The focus is on the settings where this function is, respectively, linear, quadratic, convex, or differentiable. Time permitting, topics such as nonsmooth, integer, vector, and dynamic optimization may be briefly addressed. Materials will include basic duality theory, optimality conditions, and intractability results, as well as algorithms and applications.



Location: Eckhart Hall, Room 133.

Times: Tue & Thu, 3:00–4:20pm

Course staff

Instructor: Lek-Heng Lim
Office: Jones 122B
Tel: (773) 702-4263
Office hours: Two 1.5-hour sessions before problem set is due, Jones 122B

Course Assistant: Vivak Patel
Office: Ryerson N375
Office hours: 3:00–3:50pm, Harper Memorial 150


Problem Sets

Collaborations are permitted but you will need to write up your own solutions and declare your collaborators. The problem sets are designed to get progressively more difficult. You will get at least six days for each problem set.

You are required to implement your own programs for problems that require some amount of simple coding (using Matlab, Mathematica, R, or SciPy).

Bug report on the problem sets: lekheng(at)

Supplementary materials

Grades and Midterms

Grade composition: 60% Problem Sets, 40% Midterms.

Midterm exams: Midterm I on Apr 28, 3:00–4:20pm, Eckhart 133. Midterm II on May 19, 3:00–4:20pm, Eckhart 133. Closed book, closed notes, no cheat sheet.


We will not use any specific textbook but will use selected material from the following references, all of which would be accessible to undergraduates.

You may download all these books online from an UChicago IP address or via ProxyIt! if you are off-campus.