Kungl Tekniska högskolan / Optimization and Systems Theory /

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SF2822 Applied Nonlinear Optimization, 7.5hp, 2016/2017

Instructor and examiner

Anders Forsgren (andersf@kth.se), room 3533, Lindstedtsv. 25, tel 790 71 27.
Office hours: Monday 11-12. (Or by agreement.)

Exercise leader and project leader

Axel Ringh (aringh@kth.se), room 3734, Lindstedtsv. 25, tel. 790 66 59.
Office hours: By agreement.

Course material

  • Linear and Nonlinear Optimization, second edition, by I. Griva, S. G. Nash och A. Sofer, SIAM, 2009.
    (The book can be ordered from several places. Please note that you can become a SIAM member for free and obtain a discount at the SIAM bookstore.)
  • Exercises in applied nonlinear optimization, 2016/2017. Available via Canvas.
  • Supplementary course material in applied nonlinear optimization, 2016/2017. Available via Canvas.
  • Lecture notes in applied nonlinear optimization, 2016/2017. Can be downloaded from this web page, see the schedule below. Also available via Canvas.
  • GAMS, A user's guide. May be downloaded from the GAMS web site.
  • GAMS. GAMS is installed in the KTH linux computer rooms. It may also be downloaded from the GAMS web site for use on a personal computer.
  • Two project assignments that are handed out during the course, March 30 and April 27 respectively.

Additional notes that may be handed out during the course are also included.

Course goals

After completed course, the student should be able to:
  • explain fundamental concepts of nonlinear programming;
  • explain how fundamental methods for nonlinear programming work;
  • illustrate how these methods work by solving small problems by hand calculations;
  • starting from a suitably modified real problem, formulate a nonlinear program; make a model in a modeling language and solve the problem;
  • analyze the solutions of the optimization problem solved, and present the analysis in writing as well as orally;
  • interact with other students when modeling and analyzing the optimization problems.

Examination

The examination is in two parts, projects and final exam. To pass the course, the following is required:
  • Pass project assignment 1, with presence at compulsory presentation lecture on Thursday April 27, and presence at the following dicussion session.
  • Pass project assignment 2, with presence at compulsory presentation lecture on Wednesday May 17, and presence at the following dicussion session.
  • Pass final exam.

Course registration

Due to the project based nature of this course, students must register no later than March 28. Registration is made by the students online following KTH standard procedures. PhD students are not able to register online but register via e-mail to Anders Forsgren.

Project assignments

The project assignments are performed in groups, where the instructor determines the division of groups. This division is changed between the two assignments. Assignment 1 is carried out using the modeling language GAMS. For project 2, there is a choice between a modeling assignment, to be carried out using GAMS, or a method assignment, to be carried out using Matlab. The project assignments must be carried out during the duration of the course and completed by the above mentioned presentation lectures. Presence at the presentation lectures is compulsory. For passing the projects, the following requirements must be fulfilled:
  • No later than the night before the presentation lecture, each group must hand in a well-written report which describes the exercise and the group's suggestion for solving the exercise. Suitable word processor should be used. The report should be on a level suitable for another participant in the course who is not familiar with the group's specific problem.
  • When handing in the report, each student should append an individual sheet with a brief self-assessment of his/her contribution to the project work, quantitatively as well as qualitatively.
  • At the presentation lecture, all assignments will be presented and discussed. Each student is expected to be able to present the assignment of his/her group. In particular, each student is expected to take part in the discussion. The presentation and discussion should be on a level such that students having had the same assignment can discuss, and students not having had the same assignment can understand the issues that have arisen and how they have been solved.
  • Each group should make an appointment for a discussion session with the course leaders. There is no presentation at this session, but these sessions are in the form of a 20 minutes question session, one group at a time. There will be times available the days after the presentation session. One week prior to the presentation lecture, a list of available times for discussion sessions will be made available at Doodle, reachable from the course home page. Each group should sign up for a discussion session prior to the presentation lecture.
  • Each participant in the course must contribute to the work of the group. Each group must solve their task independently. Discussion between the groups is encouraged, but each group must individually solve the assignments. It is not allowed to use solutions made by others in any form. If these rules are violated, disciplinary actions in accordance with the KTH regulations will be taken.

Each project assignment is awarded a grade which is either fail or pass with grading E, D, C, B and A. Here, the mathematical treatment of the problem as well as the report and the oral presentation or discussion is taken into account. Normally, the same grade is given to all members of a group.

Final exam

The final exam consists of five exercises and gives a maximum of 50 points. At the exam, the grades F, Fx, E, D, C, B and A are awarded. For a passing grade, normally at least 22 points are required. At the exam, in addidion to writing material, no other material is allowed at the exam. Normally, the grade limits are given by E (22-24), D (25-30), C (31-36), B (37-42) and A (43-50).

The grade Fx is normally given for 20 or 21 points on the final exam. An Fx grade may be converted to an E grade by a successful completion of two supplementary exercises, that the student must complete independently. One exercise among the theory exercises handed out during the course, and one exercise which is similar to one exercise of the exam. These exercises are selected by the instructor, individually for each student. Solutions have to be handed in to the instructor and also explained orally within three weeks of the date of notification of grades.

The final exam is given Thursday June 1, 8.00-13.00.

Final grade

By identitying A=7, B=6, C=5, D=4, E=3, the final grade is given as

round( (grade on proj 1) + (grade on proj 2) + 2 * (grade on final exam) ) / 4),

where the rounding is made to nearest larger integer in case of a tie.

Preliminary schedule

(Lecture notes are not yet available.)

"L" means lecture, "E" means exercise session, "P" means project sesstion.
Type Day Date Time Room Subject
L1.Wed Mar 22 8-10 E51 Introduction. Nonlinear programming models. (pdf)
L2.Thu Mar 23 10-12 Q21 Optimality conditions for linearly constrained problems. (pdf)
L3.Fri Mar 24 13-15 L52 Optimality conditions for nonlinearly constrained problems. (pdf)
P1.Wed Mar 29 8-10 E31 Introduction to GAMS.
P2.Thu Mar 30 10-12 GAMS excercise session.
E1.Fri Mar 31 13-15 D34 Optimality conditions.
L4.Wed Apr 5 8-10 D34 Unconstrained optimization. (pdf)
L5.Thu Apr 6 10-12 Q21 Unconstrained optimization, cont. (pdf)
L6.Fri Apr 7 13-15 E51 Equality-constrained quadratic programming. (pdf)
E2.Wed Apr 19 8-10 D34 Unconstrained optimization.
E3.Thu Apr 20 10-12 E31 Equality-constrained quadratic programming.
L7.Fri Apr 21 13-15 E51 Inequality-constrained quadratic programming. (pdf)
L8.Wed Apr 26 8-10 E31 Inequality-constrained quadratic programming, cont.
(pdf)
P3.Thu Apr 27 10-12 D34 Presentation of project assignment 1.
E4.Fri Apr 28 13-15 D34 Inequality-constrained quadratic programming.
L9.Wed May 3 8-10 E51 Sequential quadratic programming. (pdf)
E5.Thu May 4 10-12 D34 Sequential quadratic programming.
L10.Fri May 5 13-15 E31 Interior methods for nonlinear programming. (pdf)
E6.Wed May 10 8-10 D34 Interior methods for nonlinear programming.
L11.Thu May 11 10-12 E31 Interior methods for nonlinear programming, cont. Semidefinite programming. (pdf)
L12.Fri May 12 13-15 E31 Semidefinite programming, cont.
P4.Wed May 17 8-10 E31 Presentation of project assignment 2.
E7.Thu May 18 10-12 E51 Semidefinite programming.
E8.Fri May 19 13-15 D34 Selected topics.

Overview of course contents

  • Unconstrained optimization
    Fundamental theory, in particular optimality conditions.
    Linesearch algorithms, steepest descent, Newton's method.
    Conjugate directions and the conjugate gradient method.
    Quasi-Newton methods.
    (Chapters 11, 12.1-12.3 and 13.1-13.2 in Griva, Nash and Sofer.)
  • Constrained nonlinear optimization
    Fundamental theory, optimality conditions, Lagrange multipliers and sensitivity analysis.
    Quadratic programming.
    Primal methods, in particular active-set methods.
    Penalty and barrier methods, in particular primal-dual interior methods.
    Dulal methods, local duality, separable problems.
    Lagrange methods, in particular sequential quadratic programming.
    (Chapters 3, 14.1-14.7, 14.8.1, 15.1-15.5, 16.1-16.3 and 16.7 in Griva, Nash and Sofer.)
  • Semidefinite programming
    Fundamental theory.
    (Chapter 16.8 in Griva, Nash and Sofer. Separate article in the supplementary course material. Fundamental concepts only.)

Welcome to the course!

Course web page: http://www.math.kth.se/optsyst/grundutbildning/kurser/SF2822/.


Optimization and Systems Theory, KTH
Anders Forsgren, andersf@kth.se