Credits: 5

Schedule: 20.02.2017 - 31.03.2017

Teaching Period (valid 01.08.2018-31.07.2020): 

IV Spring (2018-2019, 2019-2020)

Learning Outcomes (valid 01.08.2018-31.07.2020): 

Building of optimization models, basic theory and main algorithms.

Content (valid 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.

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Interactive participation to the course, or exam.

Workload (valid 01.08.2018-31.07.2020): 

Contact hours 48h, attendance is not obligatory
Voluntary homework 10h
Autonomous studies 30h

Study Material (valid 01.08.2018-31.07.2020): 

Lecture notes. H. A. Taha: Operations Research, An Introduction , Prentice-Hall International

Substitutes for Courses (valid 01.08.2018-31.07.2020): 

Mat-2.2105 Introduction to Optimization

Course Homepage (valid 01.08.2018-31.07.2020):

Prerequisites (valid 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.

Grading Scale (valid 01.08.2018-31.07.2020):