Heuristic Algorithms for Combinatorial Optimization ProblemsDF15700, 2010HT
Doctoral students in computer science and computer systems.
The course was last given
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 system design and software engineering, will be discussed.
Undergraduate courses in algorithms and complexity theory. Basic knowledges in system design or software engineering.
· Introduction to combinatorial optimization problems.
· Basic principles of heuristic techniques.
· Simulated annealing.
· Tabu search.
· Genetic algorithms.
· Lagrangean relaxation.
· Application of heuristic techniques.
· Project work.
The course consists of two parts, the lecture part and the project part. The lecture part 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. In the project part, a student will implement one or two heuristic algorithms for a practical problem. The implementation and the experimental results will be documented in a term paper.
Lecture notes and articles.
Petru Eles and Zebo Peng
Project work and term paper
Linköping University, ESLAB
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