prof. RNDr. Ing. Miloš Šeda, Ph.D.
E-mail:   seda@fme.vutbr.cz  WWW:   http://www.uai.fme.vutbr.cz/~mseda/ Dept.:   Institute of Automation and Computer Science Dept. of Applied Computer Science Position:   Professor Room:   A1/0640

Supervised courses:

• Automation (6AA)
• Automation (6AA)
• Automation (6AA-A)
• Automation (6AA-A)
• Control Theory I (VA1)
• Control Theory I (VA1-K)
• Control Theory II (VA2)
• Control Theory II (VA2-K)
• Database Systems (VDS)
• Database Systems and Cloud Storages (VDC)
• Database Systems and Cloud Storages (VDC-K)
• Graph Algorithms (9GRA)
• Introduction to Automatic Control (VZR)
• Introduction to Automatic Control (VZR-K)
• Mathematical Principles of Computer Science (VZI)
• Mathematical Principles of Computer Science (VZI-A)
• Mathematical Principles of Computer Science (VZI-K)
• Optimization Methods I (FOA)
• Optimization Methods I (FOA-A)
• Optimization Methods I (FOA-K)

Publications:

• ŠEDA, M.; ŠEDA, P.:
  Minimised Weighted Covering of Service Networks,
  Proceedings of the 17th International Carpathian Control Conference ICCC 2016, pp.645-650, ISBN 978-1-4673-8605-0, (2016), Technical University Košice
  conference paper
  akce: 17th INTERNATIONAL CARPATHIAN CONTROL CONFERENCE, ICCC´2016, Tatranská Lomnica, 29.05.2016-01.06.2016
• ŠEDA, M.; ŠEDA, P.:
  A Minimisation of Network Covering Services in a Threshold Distance,
  Recent Advances in Soft Computing, pp.159-169, ISBN 978-3-319-19823-1, (2015), Springer
  book chapter
• ŠEDA, M.:
  Computational Geometry and Heuristic Approaches for Location Problems,
  K. Chan, J. Yeh (eds.): Proceedings of the International Conference of Electrical, Automation and Mechanical Engineering EAME 2015, pp.545-549, ISBN 9789462520714, (2015), Atlantis Press
  conference paper
  akce: International Conference of Electrical, Automation and Mechanical Engineering EAME 2015, Phuket, Thailand, 26.07.2015-27.07.2015
• ŠEDA, M.; ROUPEC, J.; ŠEDOVÁ, J.:
  Transportation Problem and Related Tasks with Application in Agriculture,
  International Journal of Applied Mathematics and Informatics, Vol.8, (2014), No.1, pp.26-33, ISSN 2074-1278
  journal article - other
• OŠMERA, P.; ŠEDA, M.; WEISSER, R.:
  Evolutionary Optimization of Controllers,
  Zelinka, I., Snášel, V., Abraham, A. (eds.): Handbook of Optimization. From Classical to Modern Approach., pp.869-887, ISBN 978-3-642-30503-0, (2012), Springer-Verlag
  book chapter
• ŠEDA, M.:
  Graph and Geometric Algorithms and Efficient Data Structures,
  Zelinka, I., Snášel, V., Abraham, A. (eds.): Handbook of Optimization. From Classical to Modern Approach., pp.73-95, ISBN 978-3-642-30503-0, (2012), Springer-Verlag
  book chapter
• MAUDER, T.; ŠANDERA, Č.; ŠTĚTINA, J.; ŠEDA, M.:
  Optimization of Quality of Continuously Cast Steel Slabs by Using Firefly Algorithm, Inštitut za kovinske materiale tehnologije
  journal article in Web of Science
• ŠEDA, M.; OŠMERA, P.:
  Systems with Queueing and Their Simulation,
  World Academy of Science, Engineering and Technology, Vol.2011, (2011), No.73, pp.713-719, ISSN 1307-6892, WASET
  journal article - other

List of publications at Portal BUT

Abstracts of most important papers:

• ŠEDA, M.; OŠMERA, P.:
  Systems with Queueing and Their Simulation,
  World Academy of Science, Engineering and Technology, Vol.2011, (2011), No.73, pp.713-719, ISSN 1307-6892, WASET
  journal article - other
  In the queueing theory, it is assumed that customer arrivals correspond to a Poisson process and service time has the exponential distribution. Using these assumptions, the behaviour of the queueing system can be described by means of Markov chains and it is possible to derive the characteristics of the system. In the paper, these theoretical approaches are presented on several types of systems and it is also shown how to compute the characteristics in a situation when these assumptions are not satisfied.
• ZELINKA, I.; OPLATKOVÁ, Z.; ŠEDA, M.; OŠMERA, P.; VČELAŘ, F.:
  Evoluční výpočetní techniky. Principy a aplikace.,
  ISBN 978-80-7300-218-3, (2008), BEN - technická literatura
  book
  This book deals with classical and modern evolutionary algorithms as genetic algorithms, differential evolution, simulated annealing, swarm intelligence etc. It obtains both theoretical and practical part. The theoretical part will make readers familiar with mathematical principles and their applications in various areas of research and industry. More advanced techniques are also studied in the book, e.g. genetic programming or grammatical evolution. Examples of realized algorithms are available on-line on web pages where readers may do their own simulations and computations without knowledge of a specific programming language.
• ŠEDA, M.:
  From Exact Methods to Heuristics,
  Vědecké spisy Vysokého učení technického v Brně Edice Habilitační a inaugurační spisy, Vol.2008, (2008), No.276, pp.1-40, ISSN 1213-418X, VUTIUM
  journal article - other
  In this work, typical problems of manufacturing-process scheduling, logical circuit design, network optimisation and robotics were described. We focused on problems of combinatorial nature or on those that can be reduced to problems of combinatorial optimization. It was shown that, for small instances, deterministic methods such as the branch-and-bound method and, in a special case, the dynamic programming approach may also be used. On the other hand, due to NP-completeness, the branch-and-bound method and dynamic-programming approach are not efficient in solving these problems if they have a high number of input parameters because of the exponentially growing time in branch-and-bound method calculations and high memory requirements for static arrays in the dynamic-programming approach. We verified that commercial software tools, such as GAMS, fail for large instances of these problems, too. In these cases, we chose heuristic techniques, mainly stochastic heuristics (or metaheuristics) that define a general framework for computations and the user must find suitable problem-specific parameter settings and verify them using benchmarks. A genetic algorithm was found to work efficiently in many situations. It provides good results in a reasonable amount of time for hundreds of input parameters and tens of capacity constraints. Finally, we showed that using stochastic heuristics need not be the only way of solving NP-complete problems and proposed approaches based on geometric data structures such as Delaunay triangulation and Voronoi diagrams. They were applied in network optimisation to find a minimal Euclidean Steiner tree and in robotics to plan trajectories of a moving object in a scene with obstacles. While being able to provide good approximations of the optimum, the proposed deterministic heuristics do not require so much tuning as stochastic heuristics and, moreover, they run in a polynomial time. Therefore they are also applicable in real time computation. Using generalised Voronoi diagrams gives an efficient tool for robot motion planning and generates smooth trajectories in a scene with movable obstacles.
• ŠEDA, M.:
  Mathematical Models of Flow Shop and Job Shop Scheduling Problems,
  International Journal of Applied Mathematics and Computer Science, Vol.4, (2007), No.4, pp.241-246, ISSN 1307-6906
  journal article - other
  In this paper, mathematical models for permutation flow shop scheduling and job shop scheduling problems are proposed. The first problem is based on a mixed integer programming model. As the problem is NP-complete, this model can only be used for smaller instances where an optimal solution can be computed. For large instances, another model is proposed which is suitable for solving the problem by stochastic heuristic methods. For the job shop scheduling problem, a mathematical model and its main representation schemes are presented.
• ŠEDA, M.:
  Heuristic Set-Covering-Based Postprocessing for Improving the Quine-McCluskey Method,
  International Journal of Computational Intelligence, Vol.4, (2007), No.2, pp.139-143, ISSN 1304-2386
  journal article - other
  Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.