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Department of Information Technology

CT - Constraint Technology for Solving Combinatorial Problems (course 1DL023) - Autumn 2008

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For administrative reasons, attendance at the first two-hour-lecture is mandatory: you must contact Pierre Flener if you cannot make it, for some very good and documentable reason, ideally in advance.

Aim of the Course

Constraint technology proposes a novel set of techniques and tools for efficiently solving (hard) combinatorial problems. Doing so is crucial in many application domains, such as scheduling, planning, molecular biology, finance, linguistics, and so on. Many companies are successfully deploying constraint technology, making knowledge thereof a marketable asset. This course combines coverage of theoretical foundations with hands-on experience in modelling and solving real-life combinatorial problems.

Constraint technology has been identified by the Association for Computing Machinery (ACM), which is a leading professional body in information technology, as a strategic direction in computing research.

Target Group

Natural-science students (biology, bioinformatics, physics, chemistry, ...), mathematics students, engineering students, finance students, linguistics students, computer-science students, and anyone interested in solving complex problems that have many constraints. Note that constraint technology is complementary to linear programming (a common technique in operations research): this course will be of particular interest to students with such a background. The target audience includes third-year and fourth-year undergraduate students, as well as graduate students.


60 higher-education credits (that is 60 ECTS points) in science, technology, systems science, or linguistics, including 12 higher-education credits (that is 12 ECTS points) in programming and basic algebra. Programming skills in Java are assumed.

Updated  2009-08-03 14:47:33 by Pierre Flener.