Teachers:
Lars Vretare, room MH:560, phone 046-222 85 35, email lv@maths.lth.se
Anders Holst, room MH:321, phone 046-222 34 05, email ah@maths.lth.se
Lectures:
Monday 15.15 MA:3 Wednesday 8.15 MA:3 Lars Vretare
Problem solving classes:
| FED | Tuesday 15.15 | MH:329 | Lars Vretare |
| I | Tuesday 15.15 | MH:331 | Anders Holst |
| FED | Thursday 15.15 | MH:333 | Lars Vretare |
Computer laboratory exercises:
There will
be two compulsory labs,the first one in the third
week and the second one in the fifth week. A schedule where you can sign
up will appear one week before the lab at the department's notice board on the ground
floor in the Mathematics building.
Assignment:
Problems for the assignment will be handed out at the second lab. Please note that the last day to get your report approved is November 25. This means that you have to hand it in earlier to be able to make necessary corrections.
Written examination:
October 25 at 8.00-13.00 or January 12 at 14.00-19.00
Literature:
Lars-Christer Böiers: Lectures on Optimization, 2001 ch. 1-9 except ch. 7.5. (KFS)
Lars-Christer Böiers: Exercises in Optimization, 2001. (KFS)
Computer Laboratory Exercises in Optimization, 2003. (handed out)
If you are not familiar with Matlab, which will be used in the labs as well as in the assignment, either you can print out a copy of the short introduction
K Sigmon: Matlab Primer
or you can buy the very useful handbook
Eva Pärt-Enander & Anders Sjöberg: Användarhandledning för MATLAB 6
| 1/9 | Introduktion (Chapter 1). Line search (Chapter 2). |
| 2/9 | 2:1,2,3,4,5 1:10b,2ae,3,4,5 |
| 3/9 | Multidimensional search: Steepest descent, Newton's method, modified Newton methods (3.1-3.4) |
| 8/9 | Some matrix theory. (Appendix A). Conjugate directions. (3.5.1-3.5.2) |
| 9/9 | 1:13 A:1,2,5 3:1,3,7,9,11 1:11 |
| 10/9 | Methods using conjugate directions. The least squares problem. (3.5-3.7) |
| 15/9 | Convex sets. (4.1-4.2) Farkas' theorem. Cones. (4.3-4.5) |
| 16/9 | 3:13,15,17,18,20 4:5,6,7,8,11,12 |
| 17/9 | Linear programming. (5.1-5.2) |
| 22/9 | Linear programming. (5.2-5.4) |
| 23/9 | 4:17,19 5:6,7,8,13,14 |
| 24/9 | Convex functions. (6.1-6.2) |
| 29/9 | Optimization of convex functions. (6.3-6.4). Introduction to constrained optimization. (7.1-7.2) |
| 30/9 | 5:15 6:2,7,8,9,10,12,17,18,19 |
| 1/10 | Constrained optimization, necessary conditions. (7.2-7.3) |
| 6/10 | Constrained optimization; sufficient conditions. (7.3-7.4) |
| 7/10 | 7:3,6,7,8,10,11,12,14,16,18,24,26 |
| 8/10 | More on constrained optimization. (7.4-7.6). Duality. (Chapter 8) |
| 13/10 | Penalty and barrier functions. (Chapter 9). |
| 14/10 | 8:1,2,4,5 9:1,3 |
| 15/10 | Revision |