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| TAOP19 | Combinatorial Optimization, advanced course, 4 p (sw) /Kombinatorisk optimering, fk/ Advancement level: D | |
| Aim: The course constitutes a completion of TAOP13, with focus on combinatorial optimization problems that require deeper insight in linear and nonlinear programming and duality theory. The course aims to give the students (i) an exemplified orientation of some important classes of combinatorial optimization problems and applications (ii) ability in mathematical modeling of combinatorial problems as well as in classifying them with respect to their complexity (iii) knowledge about efficient algorithms and methods as well as ability in solving combinatorial optimization problems (iv) ability to modify existing algorithms and develop new ones in order to solve new problemsPrerequisites: TAOP13 Combinatorial optimization, introductory course.Course organization: The course is divided into seminars and tutorials. The seminars treat the theory necessary in developing mathematical models and combinatorial algorithms, while tutorials are largely held by the students themselves under supervision of a teacher. A number of interactive computer exercises familiarize the students with modern optimization software. Course content: Combinatorial optimization problems in communication networks and distributed computer systems, local search, tabu search, simulated annealing, genetic algorithms, nonlinear programming algorithms, Lagrangian duality, subgradient optimization.Course literature: Published Research papers (distributed during the course) Boffey, B: Distributed Computing, Blackwell, 1992 | ||
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