STAT 28000/CAAM 28000. Optimization

Department of Statistics
University of Chicago
Spring 2019

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, 3:30–4:50pm

Course staff

Instructor: Lek-Heng Lim
Office: Jones 122C
Tel: (773) 702-4263
Office hours: Two hours in weeks when a problem set is due, one hour in other weeks. Venue: Jones 122C. Times would be announced by email.

Course Assistant I: Zhipeng Lou
Office hours: 5:30–7:00pm Mon, Jones 226

Course Assistant II: Zhisheng Xiao
Office hours: 10:00–11:20am, Tue, Searle 206

Course Assistant III: Lijia Zhou
Office hours: 10:30–11:50am, Wed, Jones 304


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 quizzes

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

Quizzes: Quiz I on Thu, Apr 25, 3:30–4:50pm, Eckhart 133. Quiz II on Tue, Jun 4, 3:30–4:50pm, 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.