The Decision-Making Method in the Management of Engineering Infrastructure Reconstruction Programs Using an Adaptive Decision Support Model

Authors

  • Illia Khudiakov O.M. Beketov National University of Urban Economy in Kharkiv

DOI:

https://doi.org/10.33042/2079-424X.2023.62.2.01

Keywords:

adaptive management, decision support, program management, engineering infrastructure

Abstract

The article is devoted to the development of a decision-making method in the development and management of the architecture of engineering infrastructure reconstruction programs and the development of a hierarchical structure of works for such programs. Implementation of relevant processes occurs when using methods of modeling the system-object of reconstruction and forecasting the values of the target function using an adaptive model of decision-making support. The work investigates the direct and indirect influence of the use of the model on the groups of processes of developing and managing the architecture of the program, developing the hierarchical structure of work, the schedule of the program, as well as determining and budgeting costs. The main limitations of engineering infrastructure reconstruction programs have been determined. Five stages of implementation of the decision-making method in the development of the program architecture have been developed, which include data collection regarding the system-object of reconstruction and determination of program limitations, determination of the target state of the system in accordance with existing limitations, selection of alternative sets of equipment to be installed on the objects systems, their comparative analysis, the selection of such a set that corresponds to the smallest value of the target function and the implementation of managerial influence. The main reasons for making changes to the program architecture are also defined, the stages of implementation of the decision-making method in managing the program architecture are developed.

Author Biography

Illia Khudiakov, O.M. Beketov National University of Urban Economy in Kharkiv

Postgraduate student

References

Argent, R.M. (2009). Components of Adaptive Management. In C. Allan, & G.H. Stankey (Eds.). Adaptive Environmental Management: A Practicioner's Guide (1st ed., pp. 11-36). Dordrecht, Netherlands: Springer Dordrecht. doi: 10.1007/978-1-4020-9632-7.

G. Blokdyk (2018). Adaptive Program Management a Clear and Concise Reference. Toronto, ON: 5StarCooks.

A. Silber (2017). Adaptive Project Management: Leading Complex and Uncertain Projects. Trenton, GA: BoockLocker.com Inc.

R.K. Wysocki and Rudd McGary (2006). Effective Project Management. Hoboken, NJ: Wiley.

Feldbaum, A. (1960). Dual management theory I. Automatics and telemechanics, XXI(9), 1240-1249.

Feldbaum, A. (1960). Dual management theory II. Automatics and telemechanics, XXI(11), 1453-1464.

Feldbaum, A. (1961). Dual management theory III. Automatics and telemechanics, XXII(1), 3-16. url: https://www.mathnet.ru/php/archive.phtml?jrnid=at&wshow=contents&option_lang=eng.

Sukhonos, M. (2016). Dual energy infrastructure portfolio management in a dynamic environment. O.M. Beketov NUUE in Kharkiv. url: https://core.ac.uk/download/pdf/78066698.pdf.

Bolling, R. J., & Van der Wijk, K. (2019, February 5). Practice note. Adaptive programme management in fragile and complex settings. The Broker. Retrieved February 1, 2023, from https://www.thebrokeronline.eu/practice-note-adaptive-programme-management-in-fragile-and-complex-settings/.

Yang, Y.C.E., Son, K., Hung, F., & Tidwell, V. (2020). Impact of climate change on adaptive management decisions in the face of water scarcity. Journal of Hydrology, 588, article number 125015. doi: 10.1016/j.jhydrol.2020.125015 .

Bennett, N.J. (2016). Using perceptions as evidence to improve conservation and environmental management. Conservation biology, 30(3), 582-592. doi: 10.1111/cobi.12681.

Canessa, S., Ottonello, D., Rosa, G., Salvidio, S., Grasselli, E., & Oneto, F. (2019). Adaptive management of species recovery programs: A real-world application for an endangered amphibian. Biological Conservation, 236, 202-210. doi: 10.1016/j.biocon.2019.05.031.

Gutheil, L. (2020) Adaptive project management for the civil society sector: towards an academic research agenda. International Development Planning Review, 43(3). doi: 10.3828/idpr.2020.17.

Papke-Shields, K.E., & Boyer-Wright, K.M. (2017). Strategic planning characteristics applied to project management. International Journal of Project Management, 35, 169-179. doi: 10.1016/j.ijproman.2016.10.015.

Wirkus, M. (2016). Adaptive Management Approach to an Infrastructure Project. Procedia – Social and Behavioral Sciences, 226, 414-422. doi: 10.1016/j.sbspro.2016.06.206.

Ciapessoni, E., Cirio, D., Pitto, A., & Sforna, M. (2020). A quantitative methodology to assess the process of service and infrastructure recovery in power systems. Electric Power Systems Research, 189, article number 106735. doi: 10.1016/j.epsr.2020.106735.

Nieviedrov, D. (2020). Methods and Models of Environmental Impact Assessment in Critical Infrastructure Facilities Construction and Reconstruction Projects [Candidate of Sciences, National Transport University]. http://www.ntu.edu.ua/.

Çelik, M. (2016). Network restoration and recovery in humanitarian operations: Framework, literature review, and research directions. Surveys in Operations Research and Management Science, 21(2), 47-61. doi: 10.1016/j.sorms.2016.12.001.

Khudiakov, I. (2023). Formation of components of an adaptive decision-making support means in engineering infrastructure reconstruction programs management. Lighting Engineering & Power Engineering, 62(1), 12–16. https://doi.org/10.33042/2079-424X.2023.62.1.02

Project Management Institute. (2008). The Standard for Program Management (2th ed.). Project Management Institute. url: https://www.pmi.org/.

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Published

2023-08-20

How to Cite

Khudiakov, I. (2023). The Decision-Making Method in the Management of Engineering Infrastructure Reconstruction Programs Using an Adaptive Decision Support Model. Lighting Engineering & Power Engineering, 62(2), 37–43. https://doi.org/10.33042/2079-424X.2023.62.2.01

Issue

Vol. 62 No. 2 (2023): Lighting Engineering & Power Engineering

Section

Power Engineering

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