Courses Master Display 2018-2019
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Course title | Algorithms and Optimisation | |||||||||||||||||||||||||||||||||||||||
Course code | EBC4049 | |||||||||||||||||||||||||||||||||||||||
ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
Assessment | None | |||||||||||||||||||||||||||||||||||||||
Period |
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Level | Advanced | |||||||||||||||||||||||||||||||||||||||
Coordinator |
Alexander Grigoriev For more information: a.grigoriev@maastrichtuniversity.nl |
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Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
Goals |
Ability to analyse the complexity of optimization problems, and ability to design fast algorithms providing good-quality solutions for hard optimization problems.
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Description |
This course is devoted to mathematical models and solution methods for hard optimization problems. First, we study the theory of computational complexity, including the concept of P versus NP. In particular, we prove that some problems are computationally intractable. Given the complexity insights, solving such problems is a challenge. Therefore, we study the design and analysis of approximation algorithms and approximation schemes, as well as the derivation of inapproximability results. We also discuss local search frameworks such as Simulated Annealing, Genetic Algorithms and Tabu Search. The course is open ended in the sense that some topics can be chosen according to student interests. Classical problems that will be covered are, among others, scheduling, colouring, set covering, and packing.
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Literature |
"Algorithms" by Dasgupta, Papadimitriou and Vazirani (Mc Graw-Hill).
Selected chapters from several books on combinatorial optimization. Research papers. |
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Prerequisites |
Students need to have obtained a Bachelor degree in Econometrics, Operations Research, Mathematics, or Computer Science. Knowledge in optimization (Linear Programming) and basic graph theory is highly recommended. Familiarity with basic algorithms and the analysis of algorithms (runtime complexity) is certainly helpful. C++ (or Java/Python/Basic) Programming skills are also prerequisites as there will be a practical programming case.
An advanced level of English. |
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Teaching methods (indicative; course manual is definitive) | PBL / Lecture / Assignment / Groupwork | |||||||||||||||||||||||||||||||||||||||
Assessment methods (indicative; course manual is definitive) | Participation / Written Exam | |||||||||||||||||||||||||||||||||||||||
Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
This course belongs to the following programmes / specialisations |
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