Heuristic Algorithms for Combinatorial Optimization Problems
Goals:
To give an introduction to the combinatorial optimization problems and
heuristic techniques which can be used to solve them. A set of
heuristic algorithms, including simulated annealing, tabu search, and
genetic algorithms, together with their practical applications to
design automation and software engineering, will be discussed.
Contents:
· Introduction to combinatorial optimization problems.
· Basic principles of heuristic techniques.
· Simulated annealing.
· Tabu search.
· Genetic algorithms.
· Lagrangean relaxation.
· Application of heuristic techniques.
· Case studies or project work.
Organization:
The course consists of two parts. Part I will introduce the area
and the basic concepts of heuristics. It will then presents several
meta-heuristic techniques including simulated annealing, tabu
search, and genetic algorithms. This part will give 3 credit points.
The second part will be a set of seminars dealing with the
application of the heuristics in practical design problems, which
will give also 3 credit points. A student can choose to participate
in only one part of the course.
Teachers:
Petru Eles and Zebo Peng
Last modified: Wed May 17 08:34:39 CEST 2006