Application of methods of fuzzy mathematics in problems of evaluation of construction projects

Authors

DOI:

https://doi.org/10.15587/2313-8416.2019.177945

Keywords:

construction project, composite uncertainty, criteria for evaluation, effective objects, fuzzy factor

Abstract

The character of the uncertainty that accompanies the task of evaluating and comparing construction projects has been investigated. Fuzzy factors have been systematized, most often complicating the examination of projects in which the objects of construction were not finalized at the time of evaluation. Partial evaluation criteria have been formalized, which will provide a sound justification for choosing the best project in the context of compositional uncertainty. The scheme of formation of integral evaluation criterion has been offered. Models and methods of fuzzy mathematics have been used in formalizing partial and forming integral evaluation criteria

Author Biography

Serhii Kartavykh, Kyiv National University of Construction and Architecture Povitroflotskyi ave., 31, Kyiv, Ukraine, 03037

Postgraduate Student

Department of Information Technology Design and Applied Mathematics

References

DBN. V. 1.2.-2:2006 (2007). Systema zabezpechennia nadiinosti ta bezpeky budivelnykh obiektiv. Navantazhennia i vplyvy. Normy proektuvannia. Chynnyi vid 2007-01-01. Kyiv: Stal, 60. Available at: https://dbn.co.ua/load/normativy/dbn/1-1-0-753

Hnatiienko, H. M.; Durdynets, V. V., Saienko, Yu. I. (Eds.) (2000). Metody otsinky kompetentnosti spetsialistiv. Matematychni ta informatsiini problemy prohnozuvannia naslidkiv tekhnohennykh ta pryrodnykh katastrof. Sotsialno-ekonomichni naslidky tekhnohennykh ta pryrodnykh katastrof: ekspertne otsiniuvannia. Kyiv: Stylos, 260.

Isaienko, D. V. (2018). Analysis of mathematical methods to intelligent decision support systems in the field of technical regulation of construction. Management of Development of Complex Systems, 36, 95–99.

Snytiuk, V. Ye. (2000). Zadacha vyboru optymalnoi alternatyvy v umovakh kompozytsiinoi nevyznachenosti. Visnyk ChITI, 2, 140–145.

Ghoreishi, S. F., Allaire, D. L. (2016). Compositional Uncertainty Analysis via Importance Weighted Gibbs Sampling for Coupled Multidisciplinary Systems. 18th AIAA Non-Deterministic Approaches Conference. doi: http://doi.org/10.2514/6.2016-1443

DSTU-N B V.2.5-37:2008 (2008). Nastanova z proektuvannia, montuvannia ta ekspluatatsii avtomatyzovanykh system monitorynhu ta upravlinnia budivliamy i sporudamy. Available at: http://profidom.com.ua/v-2/v-2-5/1796-dstu-n-b-v-2-5-372008-nastanova-z-projektuvanna-montuvanna-ta-jekspluataciji-avtomatizovanih-sistem-monitoringu-ta-upravlinna-budivlami-i-sporudami

Ruszczyński, A., Shapiro, A. (2003). Stochastic Programming Models. Stochastic Programming, 10, 1–64. doi: http://doi.org/10.1016/s0927-0507(03)10001-1

Guimarẽes, A. C. F., Ebecken, N. F. F. (1999). FuzzyFTA: a fuzzy fault tree system for uncertainty analysis. Annals of Nuclear Energy, 26 (6), 523–532. doi: http://doi.org/10.1016/s0306-4549(98)00070-x

Isaienko, D. V., Ploskyi, V. O., Terenchuk, S. A. (2018). Formation of the fuzzy knowledge of the knowledge support system for decision-making technical regulation of construction activity. Management of Development of Complex Systems, 35, 168–174.

Kartavykh, S. A., Terenchuk, S. M. (2019). Models and methods for evaluating construction projects under conditions of compositional uncertainty. Management of Development of Complex Systems, 39, 84–89.

Snitiuk, V. E., Rifat, Mokhammed Ali (2002). Modeli processa priniatiia adaptivnykh reshenii kompozicionnoi struktury s determinirovannymi i veroiatnostnymi kharakteristikami. Radioelektronika i informatika, 4, 123–127.

Published

2019-09-26

Issue

Section

Technical Sciences