Learning Outcomes
Cognitive: the students obtain knowledge of Optimization Techniques which are exploited in several branches of Computer Science.
Skills: the students understand in depth Optimization Techniques which are necessary in several procedures and implementations of Decision Sciences and are applied in computational and communications systems.
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
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.