Course Syllabus: MATH 271A, Fall 2024

Instruction

Instructor: Jiawang Nie

Office: AP&M 5864.

Phone: (858) 534-6015.

Email: njw "AT" math . ucsd . edu.

Office hours: 3:00pm-4:00pm (Wednesdays, in office), 2:00pm-3:00pm (Fridays, in office), or after the lectures.

Lectures

Time: 3:30pm -4:50pm on TuTh.

Location: APM 2402.

TA Contact Info

Jiyoung Choi: jichoi@ucsd.edu, OHs: 10:30am-12:00pm (Thursday & Fridays, HSS 3070, in-person).

Course Description

This graduate level course will focus on basic theory and methods in numerical optimization. The topics to be convered include: unconstrained optimization and optimality conditions, gradient and Newton methods, quasi-Newton methods, constrained optimization, Karush-Kuhn-Tucker conditions, linear and quadratic programming; interior methods; penalty and barrier function methods; basic duality theory.

Prerequisite

Basic training in real analysis and linear algebra, or consent by the instructor.

Textbook

There are no required textbooks. The recommended ones are:
Nonlinear Programming by Dimitri Bertsekas;
Numerical Optimization by Jorge Nocedal and Stephen Wright;
Practical Optimization by Philip Gill, Walter Murray and Margaret Wright.

Assignments

Homework will be assigned regularly. Details about completing homework will be given in class. Please write your names, ID nubmers, and section numbers on your homework.

Exams

There is no final exam scheduled for this course.

Grading

The grade will be based on the performance of completing homework assignments and attendance to lectures.

Academic Integrity

Every student is expected to conduct themselves with academic integrity. Any kind of cheatings is not allowed in this course. Violations of academic integrity will be treated seriously.

See UCSD Policy on Integrity of Scholarship.