Improvement of organizational and logistics processes in civil construction based on adaptive stochastic models
DOI:
https://doi.org/10.32347/2707-501x.2026.57(1).57-63Keywords:
construction logistics, construction organization, stochasticity, Just-in-Case, NSGA-II, Dynamic TOPSIS, entropy, supply chain resilienceAbstract
The article substantiates the scientific and methodological foundations for improving organizational processes in civil construction through the implementation of adaptive logistics models. The relevance of the study is driven by the functioning of the industry under conditions of extreme stochasticity (BANI-world), where traditional deterministic planning methods and the "Just-in-Time" strategy demonstrate systemic vulnerability. The scientific novelty of the work lies in the development of a comprehensive mathematical apparatus for material flow management based on the principles of organizational homeostasis and information entropy minimization. Shannon entropy is used for quantitative assessment of project reliability and the initiation of adaptive management measures. Stochastic demand is formalized based on the Wiener process, and parameters for dynamic safety stocks within the "Just-in-Case" strategy are calculated, allowing the system to absorb logistical shocks without disrupting the technological rhythm. Organizational planning is presented as a RCPSP problem with stochastic resource availability, considering the Preemptive Resume service discipline. The interaction of inbound and outbound flows is described using queuing theory Q-schemes and stochastic differential equations with reflection, ensuring non-negativity of stock levels. The NSGA-II evolutionary algorithm is applied for multi-objective optimization across time, cost, and entropy vectors. The selection of a rational solution from the Pareto front is implemented via the Dynamic TOPSIS method with adaptive entropy weights, enabling the system to react instantaneously to changes in market and security factors. Organizational resilience tools are proposed, including a network of construction consolidation centers (CCC), reverse logistics mechanisms, and contractual models such as Open Book and GMP. The implementation of the developed model ensures a reduction in logistics costs by 15–20% and increases the transparency of reconstruction in Ukraine.
References
Cascio J. Facing the Age of Chaos. Anthropocene Magazine. 2020. URL: https://www.anthropocenemagazine.org/2020/04/facing-the-age-of-chaos/ (дата звернення: 27.11.2025).
Ponomarenko V., Iastremska O. Determining the impact of vuca-world and bani-world on the activities of enterprises in the experience economy. Decision support systems in project and program management: Collective monograph. Edited by I. Linde. European University Press. Riga: ISMA, 2024. Р. 212 – 255.
Kelley J. E., Walker M. R. Critical-Path Planning and Scheduling. Proceedings of the Eastern Joint Computer Conference. 1959. P. 160–173. URL: https://mosaicprojects.com.au/PDF/PM-History_Critical_Path_Planning_&_Scheduling_Kelley_and_Walker_1959.pdf. (дата звернення: 27.11.2025).
Koskela L. An exploration towards a production theory and its application to construction. Espoo: VTT, 2000. 296 p. URL: http://www.gpsustentavel.ufba.br/downloads/lean_construction_koskela_P408.pdf. (дата звернення: 27.11.2025).
Ivanov D., Dolgui A. A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control. 2020. Vol. 32, Iss. 9. P. 775–788. DOI:10.1080/09537287.2020.1768450
Arbabi S., Sadeghi H., Golpîra H. Sustainable construction supply chain management with stochastic material demand. Journal of Supply Chain Management. 2025. Vol. 27, No. 2. P. 19-37. URL: https://scmj.ihu.ac.ir/article_210133_8da32e7d8d1d311091dfb454a4045ba3.pdf?lang=en. (дата звернення: 27.11.2025).
Von Bertalanffy L. General System Theory: Foundations, Development, Applications. New York: George Braziller, 1968. 295 p. URL: https://monoskop.org/images/7/77/Von_Bertalanffy_Ludwig_General_System_Theory_1968.pdf. (дата звернення: 27.11.2025).
Shannon C. E. A mathematical theory of communication. The Bell System Technical Journal. 1948. Vol. 27. P. 379–423. URL: https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf. (дата звернення: 27.11.2025).
Tan N.D., Kim H.-S., Long L.N.B., Nguyen D.A., You S.-S. Optimization and inventory management under stochastic demand using metaheuristic algorithm. PLoS ONE. 2024, 19(1): e0286433. https://doi.org/10.1371/journal.pone.0286433.
Khajesaeedi M. et al. Resource-constrained project scheduling problem: review of recent developments. Journal of Project Management. 2025. Vol. 10(1). P. 1-26. DOI:10.5267/j.jpm.2024.12.002.
Gupta S., George R.C., Philip D., Nair S. Impact of activity time stochasticity on critical paths and their completion probabilities in construction projects. Building Engineering, 2025, 3(2), 1703. https://doi.org/10.59400/be1703.
Little J.D.C. A Proof for the Queuing Formula: L = λW. Operations Research, 1961, 9, 383-387. https://doi.org/10.1287/opre.9.3.383.
Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 2002, vol. 6, no. 2, pp. 182-197. DOI: 10.1109/4235.996017.
Bastanifar I., Khan K.H., Azmi S.N., Opera E. Applying dynamic TOPSIS: a multi-criteria decision-making approach to economic corridors under uncertainty-the case of IMEEC. Cogent Economics & Finance, Taylor & Francis Journals, 2025, vol. 13(1), pp. 2558028-255. DOI: 10.1080/23322039.2025.2558028
Muerza V., Guerlain C. Sustainable Construction Logistics in Urban Areas: A Framework for Assessing the Suitability of the Implementation of Construction Consolidation Centres. Sustainability, 2021, 13: 7349. DOI: 10.3390/su13137349.
