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Heuristic Algorithms for Combinatorial Optimization ProblemsDF15700, 2010HT
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Course plan
Lectures
24 hours
Recommended for
Doctoral students in computer science and computer systems.
The course was last given
Spring 2007
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 system design and software engineering, will be discussed.
Prerequisites
Undergraduate courses in algorithms and complexity theory. Basic knowledges in system design or software engineering.
Contents
· Introduction to combinatorial optimization problems.
· Basic principles of heuristic techniques.
· Simulated annealing.
· Tabu search.
· Genetic algorithms.
· Lagrangean relaxation.
· Application of heuristic techniques.
· Project work.
Organization
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.
Literature
Lecture notes and articles.
Lecturers
Petru Eles and Zebo Peng
Examiner
Zebo Peng
Examination
Project work and term paper
Credit
6 hp
Organized by
Linköping University, ESLAB
Comments
Page responsible: Director of Graduate Studies
