OPTIMIZATION

Course Information
TitleΒΕΛΤΙΣΤΟΠΟΙΗΣΗ / OPTIMIZATION
CodeNGE-06-02
FacultySciences
SchoolInformatics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorNikolaos Tsitsas
CommonNo
StatusActive
Course ID40002959

Programme of Study: Undergradute Studies - School of Informatics (2015-today)

Registered students: 25
OrientationAttendance TypeSemesterYearECTS
Information SystemsGeneral Electives635
Digital MediaElective Courses635
Communication, Networks And Systems ArchitectureGeneral Electives635
Information And Communication Technologies In EducationGeneral Electives635
General Common DirectionGeneral Electives635

Class Information
Academic Year2015 – 2016
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
600004988
Type of the Course
  • Background
  • General Knowledge
Course Category
General Foundation
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
Knowledge of methodologies and techniques in Optimization and using them in applications of Computer Science
General Competences
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
Course Content (Syllabus)
-- Introduction and motivation with examples and applications -- Basic notions. Optimization algorithms, theorems and rate of convergence -- Optimization of non-linear problems with and without constraints -- Implementations with mathematical software
Keywords
Nonlinear Optimization, Optimization Algorithms
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
Description
There is a web page for the course in elearning
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures391.3
Reading Assigment301
Project481.6
Exams30.1
Literature Study301
Total1505
Student Assessment
Description
There will be two tests and the students can pass the course if they have grade greater than 5 in each one of these tests. Also, projects will be assigned with bonus on the final grade from 0 to 2 points (depending on the quality each project).
Student Assessment methods
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
1. Μη γραμμικές μέθοδοι βελτιστοποίησης Μεθοδολογία και αλγόριθμοι, Βασιλείου Παναγιώτης - Χρήστος, Γεωργίου Αθανάσιος, 960-431-248-0, Ζήτη 1993, 1η έκδ., 11113. 2. Τεχνικές βελτιστοποίησης, Ροβιθάκης Γεώργιος Α., 978-960-418-141-4, Τζιόλα 2007, 1η εκδ., 18549025.
Last Update
07-06-2016