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Higher education teachers: Košir Andrej
Collaborators: Kunaver Matevž
Prerequisits:
Content (Syllabus outline):
Algorithms, time and memory complexity, data structures. Graph theory (representation, selected graph properties, basic graph algorithms). Introduction to operations research and optimization. Optimization task (formulation, objective function, and set of solutions). Linear and integer programming (simplex method, selected known problems). Network analysis (maximal flow, minimal cost, shortest path). Nonlinear optimization (gradient and Newton method, constraint optimization). Combinatorial optimization. Game theory. Markov chains (classification of states, ergodicity). Time series. Queuing theory. Heuristic optimization techniques. Measuring QoE and user opinion. Basics of business intelligence in TC. Selected optimization problems in telecommunications (topology design, optimal resource assignment, optimal routing, yield management).
Objectives and competences:
Basic understanding of optimization problem formulation and solving. Understanding the relationship between problem formulation and computer aided solving. Recognizing the optimization problem type related to existing computer solvers. Understanding end user satisfaction together with business model in term of optimization objective function.
Intended learning outcomes:
Develop and apply the conceptual basis and the practical skills in problem solving. Formulate, recognize and solve complex optimization problems. Select the appropriate optimization problem formulation and the select the optimal existing computer tool to solve it.
Learning and teaching methods: