Combinatorial Optimization

• Mathematical modeling of combinatorial optimization problems
• Techniques for solving combinatorial optimization problems
• Mathematical programming
• Constraint programming
• Branch and bound algorithms
• Branch and cut algorithms
• Approximation algorithms
• Heuristic algorithms
• Metaheuristic algorithms
• Local search methods
• Modeling and application of algorithms in practical problems of scheduling, facility location, routing, resource management, telecommunication

Upon successful completion of this course, students will:

• model combinatorial optimization problems
• recognize the difficulty of solving combinatorial optimization problems
• be familiar with the basic algorithmic techniques for solving combinatorial optimization problems
• implement exact, approximate, and heuristic algorithms for combinatorial optimization problems
• evaluate the performance of algorithms
• be aware of the recent research developments in the field of Combinatorial Optimization

None

Lectures, labs

Exercises (50%), Written final exams (100%)

1. Ιωάννης Μαρινάκης, Αθανάσιος Μυγδαλάς, Συνδυαστική Βελτιστοποίηση, Εκδόσεις Νέων Τεχνολογιών, Έκδοση: 1η/2016.
2. Ding Zhu Du, Panos Pardalos, Xiaodong Hu, Weili Wu, Εισαγωγή στη Συνδυαστική Βελτιστοποίηση, Εκδόσεις Νέων Τεχνολογιών, Έκδοση: 1η/2023.