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SF2812 Applied Linear Optimization 7,5 hp

Course memo Spring 2025-60467

Version 1 – 01/07/2025, 9:08:27 PM

Course offering

Spring 2025-60467 (Start date 14 Jan 2025, English)

Language Of Instruction

English

Offered By

SCI/Mathematics

Course memo Spring 2025

Headings denoted with an asterisk ( * ) is retrieved from the course syllabus version Spring 2022

Content and learning outcomes

Course contents

  • The simplex method and interior methods for linear programming.
  • Utilization of problem structure in linear programming, e.g., decomposition and column generation.
  • Stochastic programming: methods and utilization of problem structure.
  • Branch-and-bound methods for integer programming.
  • Lagrangian relaxation and subgradient methods for large-scale integer programming problems with special structure.

Intended learning outcomes

To pass the course, the student shall be able to:

  • Apply theory, concepts and methods from the parts of optimization that are given by the course contents to solve problems.
  • Model, formulate and analyze simplified practical problems as optimization problems and solve by making use of given software.
  • Collaborate with other students and demonstrate ability to present orally and in writing.

To receive the highest grade, the student should in addition be able to do the following:

  • Combine and explain the methods in the course, and
  • Apply and explain the theory and the concepts of the course in the practical problems that are included.

Learning activities

The main learning activities are:

  • Lectures
  • Exercise sessions
  • Two project assignments
  • Office hours

Detailed plan

Instructor and examiner

Jan Kronqvist (jankr@kth.se), Lindstedtsv. 25.
Office hours: To be decided

Exercise and project leaders

Pim Heeman, pimh@kth.se,  Lindstedtsv. 25.

Office hours: To be decided

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.) The same book is also used in SF2822.
  • Exercises in applied linear optimization, . Available via Canvas.
  • Lecture notes in applied linear optimization, Available via Canvas.
  • Theory questions in applied linear optimization, 2024/2025. Available via Canvas.
  • GAMS, A user's guide. Available at 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, January 28 and February 10 respectively.

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

Preliminary schedule

"L" means lecture, "E" means exercise session, "P" means project session.

Type Day Date Time Room Subject
L1 Wed Jan 15 15-17 U41 Introduction. Linear programming models.
L2 Thu Jan 16 10-12 U21 Linear programming. Geometry.
L3 Fri Jan 17 8-10 U31 Lagrangian relaxation. Duality. LP optimality.
L4 Mon Jan 20 10-12 W25 Linear programming. The simplex method.
E1 Tue Jan 21 8-10 U51 Linear programming. The simplex method.
L5 Wed Jan 22 10-12 U31 More on the simplex method.
E2 Thu Jan 23 13-15 W37 Linear programming. The simplex method.
P1 Mon Jan 27 15-17 U21 Introduction to GAMS (please bring laptop).
P2 Tue Jan 28 13-15 U21 GAMS excercise session + First project.
L6 Wed Jan 29 13-15 U31 Stochastic programming.
E3 Thu Jan 30 13-15 U41 Stochastic programming.
L7 Mon Feb 3 13-15 U21 Interior methods for linear programming.
E4 Wed Feb 5 10-12 U31 Interior methods for linear programming.
L8 Thu Feb 6 13-15 U31 Integer programming models.
P3 Mon Feb 10 15-17 U21 Presentation of project assignment 1.
L9 Wed Feb 12 10-12 U21 Branch-and-bound.
E5 Thu Feb 13 10-12 W37 Integer programming.
L10 Fri Feb 14 8-10 U21 Decomposition and column generation.
E6 Mon Feb 17 15-17 U21 Decomposition and column generation.
L11 Tue Feb 18 13-15 U41 Lagrangian relaxation. Duality.
E7 Thu Feb 20 15-17 U21 Lagrangian relaxation. Duality.
P4 Mon Feb 24 13-15 U21 Presentation of project assignment 2.
L12 Wed Feb 26 10-12 U31 Subgradient methods.
E8 Thu Feb 27 13-15 U21 Subgradient methods.
L13 Mon Mar 3 13-15 U31 TBD

 

Examination

Examination

The examination is in two parts, projects and final exam. To pass the course, the following requirements must be fulfilled:

  • Pass project assignment 1, with presence at the compulsory presentation lecture on Monday February 10 and presence at the following discussion session.
  • Pass project assignment 2, with presence at the compulsory presentation lecture on Monday February 24 and presence at the following discussion session.
  • Pass final exam.

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. In addition 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 Friday March 7 2025.

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.

However, a final grade of C or higher requires at least a grade of D in the exam.

Project Assignments

The project assignments are performed in groups, where the instructor determines the division of project groups. This division is changed between the two assignments. The assignments are carried out by the modeling language GAMS. The project assignments must be carried out during the duration of the course and completed by the above mentioned presentation lectures. It is the responsibility of each student to allocate time so that the project group can meet and function. 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 project group must hand in a well-written report which describes the exercise and the project group's suggestion for solving the exercise through Canvas as a pdf file. 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.
  • At the beginning of the presentation lecture,  each student should hand in 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. The presentations and discussions will be made in small presentation groups, first in presentation groups where each student has worked on the same project assignment, and then in presentation groups where the students have worked on different project assignments. Each student is expected to be able to present the assignment of his/her project group, the modeling and the solution. 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 student should bring a copy of the project group's report to the presentation lecture, either in paper or electronically.
  • Each project group should make an appointment for a discussion session with the course leaders. There is no presentation at this session, but the course leaders will ask questions and give feedback. There will be time slots 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, announced via Canvas. Each project group should sign up for a discussion session prior to the presentation lecture.

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. The exercises are divided into basic exercises and advanced exercises. Sufficient treatment of the basic exercises gives a passing grade. Inclusion of the advanced exercises is necessary for the higher grades (typically A-C). Normally, the same grade is given to all members of a project group. A student who has not worked on the advanced exercises says so in the self assessment form.

Each project group must solve their task independently. Discussion between the project groups concerning interpretation of statements etc. are encouraged, but each project group must work independently without making use of solutions provided by others. All project groups will not be assigned the same exercises.

Preparations before course start

Literature

To be announced at the beginning of the course. Preliminary literature:

Linear and Nonlinear Programming by S.G.Nash och A.Sofer, McGraw-Hill, and some material from the department.

Examination and completion

Grading scale

A, B, C, D, E, FX, F

Examination

  • PRO1 - Project, 1.5 credits, Grading scale: A, B, C, D, E, FX, F
  • PRO2 - Project, 1.5 credits, Grading scale: A, B, C, D, E, FX, F
  • TEN1 - Examination, 4.5 credits, Grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

No information inserted

Round Facts

Start date

14 Jan 2025

Course offering

  • Spring 2025-60467

Language Of Instruction

English

Offered By

SCI/Mathematics

Contacts

Course Coordinator

Teachers

Examiner