Laajuus: 5
Aikataulu: 25.02.2019 - 09.04.2019
Opetusperiodi (voimassa 01.08.2018-31.07.2020):
IV Spring (2018-2019, 2019-2020)
Osaamistavoitteet (voimassa 01.08.2018-31.07.2020):
Building of optimization models, basic theory and main algorithms.
Sisältö (voimassa 01.08.2018-31.07.2020):
An introductory course to linear and nonlinear optimization. The following topics are included: Building of optimization models, resource allocation models, least-squares problems, goal programming, integer optimization and traveling salesman problem together with genetic algorithms. In exercises Excel and Matlab are used to solve the problems.
Toteutus, työmuodot ja arvosteluperusteet (voimassa 01.08.2018-31.07.2020):
Interactive participation to the course, or exam.
Tarkennetut arviointiperusteet ja -menetelmät ja tutustuminen arviointiin (koskee tätä kurssikertaa):
The 2019 edition of the course will have an assessment an exam at the end of the period.
The students can also take weekly online quizzes that will supplement the exam grade. The quizzes are also to exercise the content and provide feedback to the students concerning their progress.
Työmäärä toteutustavoittain (voimassa 01.08.2018-31.07.2020):
Contact hours 48h, attendance is not obligatory
Voluntary homework 10h
Autonomous studies 30h
Oppimateriaali (voimassa 01.08.2018-31.07.2020):
Lecture notes. H. A. Taha: Operations Research, An Introduction , Prentice-Hall International
Korvaavuudet (voimassa 01.08.2018-31.07.2020):
Mat-2.2105 Introduction to Optimization
Kurssin kotisivu (voimassa 01.08.2018-31.07.2020):
https://mycourses.aalto.fi/course/search.php?search=MS-C2105
Esitiedot (voimassa 01.08.2018-31.07.2020):
MS-A00XX Matrix Algebra, MS-A01XX Differential and integral calculus 1, and MS-A01XX Differential and integral calculus 2.
Arvosteluasteikko (voimassa 01.08.2018-31.07.2020):
0-5
Kurssin aikataulu (koskee tätä kurssikertaa):
| Lec1 | Introduction + Formulation |
| Lec2 | Formulation + Graphical method |
| Lec3 | Simplex method |
| Lec4 | Simplex method - special cases |
| Lec5 | Linear duality + sensitivity analysis |
| Lec6 | Integer programming - formulation |
| Lec7 | Integer programming - B&B + cutting planes |
| Lec8 | Analysis - Convexity, unconstrained opt conditions |
| Lec9 | Constrained opt: KKT conditions |
| Lec10 | Line search, Gradient and Newton |
| Lec11 | Constr. Newton and Int. Point. |
| Lec12 | Revision |
- Opettaja: Dillon Ellie
- Opettaja: Oliveira Fabricio