When and Where: TH - 11.45 am - 1.00 pm in HA 215.
My office hours: TH - 10.20-11.20 am and by appointment.
Course webpage: The official webpage for this course is located at http://www4.ncsu.edu/~kksivara/ma706/. It is your duty to check the webpage regularly for course announcements. I will also post course material, including handouts, homeworks, and exams here. The webpage should be up to date. However, please inform me about missing links, and necessary updates by sending me email.
Course prerequisites: MA/OR 505 and MA 425
Course objectives: The first part of the course covers the theory of unconstrained and constrained nonlinear optimization. The 2nd part of the course covers numerical algorithms and associated software for solving large scale nonlinear optimization problems. We will also briefly review applications of nonlinear optimization to real world problems. The theoretical part of the course will cover basic convex analysis, optimality conditions for unconstrained and constrained nonlinear optimization problems and Lagrangian duality. The algorithmic part of the course will cover line search, trust region, conjugate gradient, and quasi-Newton methods for unconstrained nonlinear optimization, and penalty and augmented Lagrangian, sequential quadratic, and barrier and interior point methods for constrained nonlinear optimization.
Course topics: The following topics will be covered in the course.
Computational resources: We will use the Optimization Toolbox in MATLAB as computer software in the course. You will be expected to write small MATLAB programs in your class project and homework assignments. Information on MATLAB is available on the course webpage and I will review some of the important features via in-class demos.
Homeworks: Homeworks are assigned every two weeks and posted on the course webpage. Some of the homework assignments will involve software assignments in MATLAB. You are encouraged to discuss your homeworks with other students, but you must must work through, write up, and turn in the assignments on your own. You must turn a hard copy of your homework in the BEGINNING OF CLASS on the due date. Late homeworks will not be accepted without a prior instructor approval. I will post the solutions to the homework assignments on the course webpage.
Exams: There is a midterm and a comprehensive final exam. The midterm exam will be held in class on Thursday, February 28, 2008. The final exam will be held in class on Tuesday, April 29th, 2008 between 8-11 am. All tests are closed book exams. As you expect, each exam has to be your own work. You will not miss an exam without a certified medical excuse or prior instructor approval. If you cannot make it to an exam, please let me know well in advance!
Class Project: You will complete a class project in the latter half of the semester on one or more aspects on the course and type a a 3-4 page report presenting the research. Early in the semester, I will designate teams of 2 individuals. You will work together and submit your research report as a team. I will assign the class project before the start of spring break.
Grading: Please make it a point to pick up your corrected homework assignments, project, and exams. The responsibility of grading the homeworks resides with Yuan (our TA). If you believe an error has been made in grading the homeworks, bring it to the attention of Yuan during his office hours. I am responsible for your class project and the exams and will notify you by email once I am done with the grading. If you detect inconsistencies in the grading notify me immediately. Project and exam scores will not be changed one week after they have been returned!
Calculation of course grade: A weighted average will be calculated as follows: Homeworks: 30 %, Midterm: 20 %, Class Project: 20 %, and Final Exam: 30 %. Homeworks are given the same weight. The grade scale is the following: 90-100 A-,A,A+; 80-89 B-,B,B+; 70-79 C-,C,C+; 60-69 D-,D,D+; below 60 F.
Course References:
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Jorge Nocedal and Stephen Wright
Numerical Optimization, 2nd edition, Springer, 2006. This will serve as the required textbook for the course. A link to the book at amazon.com. | ||
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Andrzej Ruszczynski Nonlinear
Optimization, Princeton University Press, 2006. This will serve as a recommended reference for the course material. A link to the book at amazon.com. |
Academic Integrity: Please review the guidelines posted at the following website.
Students with disabilities: "Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accomodations, students must register with Disability Services for Students at 1900 Student Health Center, Campus Box 7509, 515-7653. For more information on NC State's policy on working with students with disabilities, please see the Academic Accommodations for Students with Disabilities Regulation (REG02.20.1)".