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doc. RNDr. Petr Hliněný, Ph.D. (KTP FI MU)

lecture 2, class exercises 1, select another -,  eng angličtina

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Course objectives. This subject presents students with basic types of optimization tasks (e.g., combinatorial, linear, and integer optimization), and teaches the most common solution methods. The main focus is on explaining and understanding (not memorizing!) the presented solution methods, including their thorough mathematical background, so that the students would be able to combine these methods with other approaches in solving nonstandard optimization problems. At the end of the course students should be able to: understand and explain the network-flow algorithm, the simplex method, and the branch-and-bound algorithm; formulate suitable and sound mathematical models of practical optimization problems; and use available tools to solve these problems.

Prerequisites. Mathematical knowledge on course levels of basic linear algebra (vectors, matrices, linear equations) and discrete mathematics (relations, graphs). Introductory knowledge of topology is also welcome.