Course detail
Optimization of Processes and Projects
FSI-VPP-KAcad. year: 2016/2017
The course deals with the following topics: The basis of mathematical process theory. Optimal regulation. The principle of Bellman as a tool for optimization of multistage processes with a general non-linear criterion function. Optimum decision policy. Dynamic programming as a tool for creation of methods for a solution of the deterministic and stochastic decision optimization problems in discrete as well as continuous range and its computation aspects. Pontryagin maximum principle. Fuzzy regulation. Applications in practical problems solution in economical decisions and in technological process control. Optimization in project management in the stages of multicriteria projects selection into portfolio in case of a restricted resource, of resource scheduling in deterministic, stochastic and fuzzy case, of cost analysis of projects and monitoring the deviations between real and scheduled projects course.
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Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
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Aims
Specification of controlled education, way of implementation and compensation for absences
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Prerequisites and corequisites
Basic literature
LOOTSMA, F. A.: Fuzzy Logic for Planning and Decision Making. Kluwer Academic Publishers, Dordrecht, pp. 195, 1997. ISBN 0-7923-4681-5
WILLIAMS, T. M. (Ed.): Managing and Modelling Complex Projects. Kluwer Academic Publishers, London, pp. 257, 1997. ISBN 0-7923-4844-3.
Recommended reading
Klapka J., Piňos P.: Decision Support System for Multicriterial R and D and Information Systems Projects Selection. European Journal of Operational Research 2002, Vol. 140, is. 2, pp. 434 - 446. (EN)
Klapka J., Piňos P., Ševčík V.: Multicriterial Projects Selection (Article). Intelligent Systems Reference Library, Vol. 38 (2013), pp. 245 - 261, ISSN 1868-4394. (EN)
Navrátil P., Pekař L., Klapka J.: Possible way of control of heat output in hotwater piping system of district heating (Article). International Journal of Circuits, Systems and Signal Processing, Vol. 9 (2015), pp. 353 - 361. C. North Atlantic University Union. (EN)
Ševčík V., Klapka J.: Mathematical Method for Multicriterial Project Selection. In: Proceedings of the International Scientific Conference Quantitative Methods in Economics (Multiple Criteria Decision Making XVII). Bratislava: EKONOM, 2014, s. 269 - 275. ISBN 978-80-225-3868-8. (EN)
WALTER, J.; VEJMOLA, S.; FIALA, P.: Aplikace metod síťové analýzy v řízení a plánování. SNTL, Praha, 1989. ISBN 80-03-00101-3
Winston W.L.: Operations Research. Applications and Algorithms. Thomson - Brooks/Cole, Belmont 2004. (EN)
Classification of course in study plans
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Syllabus
2. Optimization of continuous decision process. Pontryagin's maximum principle.
3. Deterministic application of dynamic programming.
4. An example of the optimal fuzzy regulation and fuzzy control of technological processes.
5. Stochastic applications of dynamic programming.
6. Increasing of reliability of technological devices.
7. Basic notions of network analysis methods, CPM method.
8. Calculation by stochastic evaluation of activities (method PERT). A comparison of the results obtained by the method PERT with the results of the simulation methods.
9. Cost analysis of a project including application of fuzzy linear programming to the solution of two-criterion time-cost problem. Heuristic methods for scheduling with resources constraints.
10. Multicriterial projects selection. Synergistic effects and hierarchical dependencies of projects.
11. Monitoring of deviations between scheduled state and real state of project. System SSD-graph.
12. Balancing of manufacturing production belt and assembly line.
13. Scheduling of production processes.