Omfattning: 5
Tidtabel: 25.02.2019 - 09.04.2019
Undervisningsperiod (är i kraft 01.08.2018-31.07.2020):
IV Spring (2018-2019, 2019-2020)
Lärandemål (är i kraft 01.08.2018-31.07.2020):
Building of optimization models, basic theory and main algorithms.
Innehåll (är i kraft 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.
Metoder, arbetssätt och bedömningsgrunder (är i kraft 01.08.2018-31.07.2020):
Interactive participation to the course, or exam.
Närmare information om bedömningsgrunderna och -metoderna och om hur den studerande kan ta del av bedömningen (gäller denna kursomgång):
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.
Arbetsmängd (är i kraft 01.08.2018-31.07.2020):
Contact hours 48h, attendance is not obligatory
Voluntary homework 10h
Autonomous studies 30h
Studiematerial (är i kraft 01.08.2018-31.07.2020):
Lecture notes. H. A. Taha: Operations Research, An Introduction , Prentice-Hall International
Ersättande prestationer (är i kraft 01.08.2018-31.07.2020):
Mat-2.2105 Introduction to Optimization
Kursens webbplats (är i kraft 01.08.2018-31.07.2020):
https://mycourses.aalto.fi/course/search.php?search=MS-C2105
Förkunskaper (är i kraft 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.
Bedömningsskala (är i kraft 01.08.2018-31.07.2020):
0-5
Närmare information om tidtabellen (gäller denna kursomgång):
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 |