Optimization Techniques

Course Information
TitleΤεχνικές Βελτιστοποίησης / Optimization Techniques
CodeIHST202
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CoordinatorNikolaos Tsitsas
CommonNo
StatusActive
Course ID600016387

Programme of Study: PMS TECΗNOLOGIES DIADRASTIKŌN SYSTĪMATŌN (2018 éōs sīmera) MF

Registered students: 0
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization217.5

Programme of Study: PMS TECΗNOLOGIES DIADRASTIKŌN SYSTĪMATŌN (2018 éōs sīmera) PF

Registered students: 8
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization217.5

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Total Hours39
Class ID
600132016
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
  • Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Learning Outcomes
With the successful completion of this course, the students will have become familiar with Optimization techniques, which are applied in software and hardware problems in interactive systems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in an interdisciplinary team
  • Generate new research ideas
Course Content (Syllabus)
Introduction to Optimization problems with motivations, examples and applications in Computer Science. Unconstrained optimization. Line search methods. Convex Optimization. Optimization with equality and inequality constraints. Evolutionary Optimization Techniques. Discrete Optimization. Applications to Optimizations in Software and Hardware—Techniques and designs for combinatorial testing.
Keywords
Optimization Problems, Line-Search Methods, Constrained Optimization, Discrete Optimization, Optimizations in Software and Hardware, Combinatiorial Testing
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
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39
Reading Assigment50
Project100
Written assigments33
Exams3
Total225
Student Assessment
Description
50% of the grade is from a project and the other 50% is from two written exams
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Exam with Extended Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Additional bibliography for study
[1] I. Griva, S. G. Nash, A. Sofer, Linear and Nonlinear Optimization, SIAM, 2009. [2] R. Baldick, Applied Optimization, Cambridge University Press, 2006. [3] C. T. Kelley, Iterative Methods for Optimization, Society for Industrial and Applied Mathematics (SIAM), 1999. [4] J. Nocedal, S. J. Wright, Numerical Optimization, Springer, 2006. [5] Γ. Α. Ροβιθάκης, Τεχνικές βελτιστοποίησης, Εκδόσεις Τζιόλα, 2007. [6] Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 [7] Steven Galbraith, Mathematics of Public Key Cryptography, 2012
Last Update
27-01-2020