Course description
Algorithm and numerical analysis (algorithm, time and space complexity).
Graph theory (description, operations on graphs, basic graph algorithms, the properties of graphs).
Introduction to operational research and optimization. Optimization task (formulation of solutions, cost function). Linear programming and integer programming (simplex method, examples from TC). Network analysis (maximum flow, minimum price, shortest path). Nonlinear optimization (gradient methods, optimization). Markov chains (classification of states, ergodicity). Time series and traffic models, queuing theory (primary analysis). Important applications in telecommunications. Experimental design and A/B testing. Experimental design and A/B testing.
Optimal user interaction and the user-centric optimization. Measuring and modelling users, situation awarenes.
Course is carried out on study programme
2nd Cycle Postgraduate Study Programme in Electrical Engineering
Objectives and competences
Basics optimization methods and algorithms. Understanding the basic principles of optimization and its procedures with application in telecommunications. Getting to know the various options to optimize and streamline processes and procedures in telecommunications. Getting to know selected classes of optimization problems and their basic solutions.
Learning and teaching methods
Lectures provide theoretical backgrounds and basic reasoning supported by illustrative examples. Tutorials adds more examples and focus on improvement of analytical skills of students. Both methods are supported by the
Jupyter Python system and selected software optimization tools allowing hands-on learning and voluntary student’s work at home. It covers analyzable examples of optimization problems.
Intended learning outcomes
After successful completion of the course, students should be able to:
- To classify the type of the optimization problem such as linear program, nonlinear optimization etc;
- To development and design an optimization problem and its objective function based on a description of a real situation.
- To perform time and space complexity of an optimization algorithm
- To select the most appropriate method and tool based on the problem description.
- Know the role of operational research in the field of telecommunications
- Using the software and mathematical tools to solve the selected optimization task
Reference nosilca
- ASLAN OĞUZ, Evin, STRLE Gregor, KOŠIR Andrej. Multimedia ad exposure scale: measuring short-term impact of online ad exposure, Multimed Tools Appl 83, (2023). https://doi.org/10.1007/s11042-023-14401-5.
- MEŽA, Marko, KOŠIR, Janja, STRLE, Gregor, KOŠIR, Andrej. Towards automatic real-time estimation of observed learner's attention using psychophysiological and affective signals : the touch-typing study case. IEEE access, ISSN 2169-3536, 2017, vol. , str. 1-18.
- VODLAN, Tomaž, TKALČIČ, Marko, KOŠIR, Andrej. The impact of hesitation, a social signal, on a user's quality of experience in multimedia content retrieval. Multimedia tools and applications, 2015, vol. 74, no. 17, str. 6871-6896.
- DROFTINA, Uroš, ŠTULAR, Mitja, KOŠIR, Andrej. A diffusion model for churn prediction based on sociometric theory. Advances in data analysis and classification, 2015, vol. 9, iss. 3, str. 341-365.
- ODIĆ, Ante, TKALČIČ, Marko, TASIČ, Jurij F., KOŠIR, Andrej. Predicting and detecting the relevant contextual information in a movie-recommender system. Interacting with computers, 2013, vol. 25, no. 1, str. 74-90.
Study materials
- W. L. Winston: Operations research Applications and Algorithms, Brooks/Cole, 2004.
- Mauricio G.C. Resende, Panos Pardalos: Handbook of Optimization in Telecommunications, Springer, 2006.
- M. W. Carter, C. C. Price: Operations Research, A Practical Introduction, CRC Press, 2000.
- D. C. Montgomery. Design and Analysis of Experiments. John Wiley & Sons, 2008.
- A. Košir: Operacijske raziskave v telekomunikacijah, Založbe FE in FRI, 2013.