1) Ability to demonstrate in-depth knowledge of management theory methods and make optimal decisions regarding software engineering procedures and processes.
2) Ability to demonstrate in-depth knowledge of conceptual and methodological and technological foundations for developing quality software systems for decision support.
3) Apply the acquired knowledge and skills to understand the procedures for solving the problems of synthesis and analysis of elements and systems of decision support that characterize the chosen field of research.
4) To integrate and apply the acquired knowledge from different cross-curricular areas in the process of creating software systems for decision-making support to solve complex scientific and technical problems.
5) Perform mathematical modeling of management decision-making options and optimize software engineering procedures and processes.

Management theory and decision making
Intelligent decision support systems
Optimizing decision making
Methods of analysis and optimization of complex systems

Topic 1. Management theory and essence of the management process 1.1. Basic concepts and definitions of management theory 1.2. Classification of approaches in management theory 1.3. Conditions of existence of control process in complex systems 1.4. The law of the required diversity in management systems 1.5. Spheres, types, systems and management theory 1.6. Principles of management of complex systems Topic 2. Features of management decisions and methods of their substantiation 2.1. Classification of types of management decisions 2.2. Features of management decision preparation 2.3. Methods of development and justification of decisions 2.4. Mechanisms and techniques of managerial decision making 2.5. Organization of the process of implementation of management decisions 2.6. The system for monitoring the implementation of decisions Theme 3. One-criteria models of decision-making problems and methods of their optimization 3.1. The problem of optimization of decision-making in the socio-economic sphere 3.2. Basic mathematical models of single-criterion decision-making optimization problems 3.3. The problem of poor conditionality in the problems of optimization of decision-making 3.4. Coordinate finite-dimensional decision-making optimization strategies 3.5. Gradient Finite-Dimensional Decision Optimization Strategies 3.6. Dynamic models of finite-dimensional decision optimization Topic 4. Multiobjective problem models and methods for making optimal decisions 4.1. Models for setting optimal decision-making problems in the socio-economic sphere 4.2. Multicriteria models of optimal decision-making problems under certainty 4.3. Criteria for making optimal decisions under uncertainty 4.4. Multi-stage models of optimal decision making problems 4.5. Multicriteria models of decision-making problems based on complex information evaluation 4.6. Multicriteria models of optimal decision-making problems based on additional information Theme 5. Dynamic programming problems in the socio-economic sphere 5.1. Formulation of the problem of dynamic programming in the socio-economic sphere 5.2. The tasks of optimal distribution of investments 5.3. Multi-step tasks of managing production and inventory of raw materials 5.4. Discrete options pricing models 5.5. Budget set and utility functions in management tasks 5.6. Models of market equilibrium in management problems Topic 6. Modeling strategies for the behavior of competing firms in the market for product manufacturers 6.1. Mathematical model of behavior strategies of two manufacturers of the same software 6.2. Mathematical model of strategies of interaction of two firms in the market of manufacturers of one software 6.3. Models of strategies of imperfect and perfect competition in the market of software manufacturers 6.4. Models of competition strategies in the information technology market 6.5. Modeling the process of optimal economic growth for software producers 6.6. Simulation of interaction dynamics of developers of commercial and non-commercial software Topic 7. Expert systems for making optimal decisions 7.1. The concept of expert decision-making systems 7.2. Productive expert decision-making systems 7.3. Presentation and use of fuzzy knowledge 7.4. Naylor diagnostic decision-making systems 7.5. Quick Choice is a multi-criteria choice system 7.6. NEYDIS is a tool for building Nylor diagnostic expert systems

1. Aleskerov F., Khabina E., Schwartz D. Binary relations, graphs and collective solutions. - M.: HSE, 2006.
2. Bellman R., Zade L. Decision-making in vague conditions - In Sat: Issues of analysis and decision-making procedures. M: Mir, 1976, p. 172-215.
3. Borisov A. N. et al. Fuzzy information processing in decision-making systems. - M.: Radio and communications, 1989.
4. Brahman T.R. Multicriteria and the choice of alternatives in technology. - M.: Radio and communications, 1984. - 560 p.
5. Vilkas E. N., Maiminas E. Z. Solutions: theory, information, modeling. - M: Radio and communications, 1981. - 328 p.
6. Katrenko AV Research operations: a textbook with the stamp MES. - Lviv: "Magnolia-2006", 2007. - 480 p.
7. Katrenko AV System analysis of objects and processes of computerization. - Lviv: "New World - 2000", 2003. - 424 p.
8. Katrenko AV, Pasichnyk VV, Pasko VP Decision-making theory: a textbook with the MES stamp. - K.: BHV Publishing Group, 2011. - 448 p.
9. Kini R. L. Decision making under many criteria: substitutions and preferences / R. L. Kini, H. Rife. - M.: Radio and communications, 1981. - 560 p.
10. Larichev O.I. Science and the art of decision making. - M.: Nauka, 1979.- 236 p.
11. Litvak B.G. Expert information. Methods of obtaining and analysis. - M.: Radio and communications. 1982. - 420 p.
12. Borisov A.N., Williams E.R. Sukur L.Ya. Dialogue decision-making systems based on mini-computers: Information, mathematical and software. - Riga: Zinatne, 1986 .-- 195 p.
13. Moiseev N.N., Ivanilov Yu.P., Stolyarova E.M. Optimization methods. - M.: Nauka, 1978.- 352 p.
14. Elvanov L.G. Theory and practice of decision making. - M.: Economics, 1984. - 176 p.
15. Neumann J., Morgershtern O. Game theory and economic behavior: Per. from English - M.: Nauka, 1970 .-- 707 p.
16. Beregulko, N. O., & Hrytsiuk, Y. I. (2013). Project management of implementation of information security systems in the structural units of the SES of Ukraine. Bulletin of Lviv State University of Life Safety: Coll. of sciences. Proceedings, 8, 49–54. Lviv: View of the BSU BDU.
17. Grytsyuk Yu. I., Dalavsky, VS Formalization of the process of risk management of software development. Scientific Bulletin of NLTU of Ukraine. 2018, Vol. 28, No. 11. P. 135-154. https://doi.org/10.15421/40281124
18. Grytsyuk YI, Nemova OA Features of managing the process of software requirements development. Scientific Bulletin of NLTU of Ukraine: Coll. scientific-technical wash. 2018, Vol. 28, No. 8. P. 161–169. https://doi.org/10.15421/40280832
19. Hrytsiuk, Y. I., & Hrytsiuk, M. Y. (2014). Features of multiplicative minimization of partial criteria in a generalized indicator. Scientific Bulletin of NLTU of Ukraine: Coll. scientific-technical Proceedings, 24 (11), 341–353. Lviv: RVV NLTU of Ukraine.
20. Hrytsiuk, Y. I., & Zabic, M. R. (2018). Risk management of software projects. Scientific Bulletin of NLTU of Ukraine: Coll. scientific-technical Proceedings, 28 (1), 150–162. Lviv: RVV NLTU of Ukraine. https://doi.org/10.15421/40280130
21. Grytsyuk, Y. I., Malets, I. O., & Rak, T. E. (2010). Structural components of the problem of optimal control of the process of fighting forest fires. Scientific Works of the Forestry Academy of Sciences of Ukraine: Coll. of sciences. Proceedings, 8, 171–174. Lviv: RVV NLTU of Ukraine.
22. Grytsyuk, Y. I., Malets, I. O., Rak, T. E. (2010). Mathematical models of project portfolio management for improvement of life safety system. Bulletin of the National University "Lviv Polytechnic". Series: Computer Science and Information Technology, 672, 110–119. Lviv: Publishing House of NU "Lviv Polytechnic".
23. Hrytsiuk, Y. I., Rak, T. E., & Malets, I. O. (2010). Features of solving the problem of optimal control of the process of elimination of forest fires. Fire Safety: Coll. of sciences. v. LSU BDZ, 17, 51–57. Lviv: View of the BSU BDU.
24. Hrytsiuk, Y. I., Furnesa, R. M., Debopre, O. V. (1995). Organization of management of furniture enterprise in the conditions of functioning of the ARM software. UkrDLTU Scientific Bulletin: Coll. scientific-technical Proceedings, 3 (3), 49–57. Lviv: Issue of the UkrDLTU.
25. Smotr, O. O., & Hrytsiuk, Y. I. (2011). Models and methods for managing the process of forest fires. Bulletin of Lviv State University of Life Safety: Coll. of sciences. Proceedings, 5, 68–77. Lviv: View of the BSU BDU.
26. See, O. O., & Hrytsiuk, Y. I. (2012). Application of system analysis for managing the process of forest fires extinguishing. Scientific Bulletin of NLTU of Ukraine: Coll. scientific-technical Proceedings, 22 (3), 346–352. Lviv: RVV NLTU of Ukraine.
27. Smotr, O. O., & Hrytsiuk, Y. I. (2012). Models and methods for managing the process of forest fires. Bulletin of Lviv State University of Life Safety: Coll. of sciences. Proceedings, 6, 68–77. Lviv: View of the BSU BDU.
28. Stashevsky, ZP, & Hrytsiuk, YI (2013). Management of an educational project of training an information security specialist based on competency models. Bulletin of Lviv State University of Life Safety: Coll. of sciences. Proceedings, 8, 87–95. Lviv: View of the BSU BDU.

Methods of diagnosing knowledge: completing individual homework assignments given in practical classes, performing individual research tasks, examination work.
Criteria for evaluating student learning outcomes:
Maximum score in points 100
Current control: 45
Homeworks 20
research task 20
examination control: 60
written component 50
oral component 10