Planning of construction supply system in constrained conditions using the dynamic programming method
https://doi.org/10.22227/1997-0935.2024.12.2001-2013
Abstract
Introduction. The application of the dynamic programming method is widely used to solve optimization problems in construction. Depending on the complexity of the project and the conditions during the construction of buildings and structures, making optimal decisions may require the analysis of a large amount of data and options. Dynamic programming allows you to consider an optimization problem as a sequence of subproblems that can be solved separately and then combined into an overall solution. This makes it possible to simplify the process of planning and project management, which is relevant for making organizational and technological decisions in the material and technical supply of construction in dense urban areas, as well as for increasing the efficiency and competitiveness of the construction industry as a whole.
Materials and methods. The study uses the method of mathematical formalization of conditions, efficient supply of resources, the method of dynamic programming and the method of graph interpretation of results.
Results. The supply system for construction production was optimized for multi-threaded organization of work; based on the optimization results, the optimal distribution of resources was determined and a network diagram of the movement of cargo flows was constructed during the considered stage of building construction. An algorithm was developed for planning the supply schedule for the continuous method of delivering resources to the construction site.
Conclusions. The organization of resource support for construction and installation work in cramped conditions must take into account a number of restrictions caused by these conditions. Reducing inventory is critical to maintaining a stock-free supply chain. In addition, with the continuous construction method, there is a risk of increasing inventory due to the dynamics of demand for materials and equipment while work is carried out in parallel. The use of the dynamic programming method made it possible at the planning stage to avoid the occurrence of shortages and exceeding the maximum stock of material resources and to select their optimal distribution at the considered stage of construction and installation work.
About the Authors
Ya. D. AgeevaRussian Federation
Yaroslava D. Ageeva — Assistant of the Department of Technology and Organization of Construction
113 Leningradskaya st., Novosibirsk, 630008
Yu. A. Chirkunov
Russian Federation
Yuri A. Chirkunov — Doctor of Physical and Mathematical Sciences, Associate Professor, Head of the Department of Higher Mathematics
113 Leningradskaya st., Novosibirsk, 630008
Scopus: 18433752300
A. A. Lapidus
Russian Federation
Azariy A. Lapidus — Doctor of Technical Sciences, Professor, Head of the Department of Technology and Organization of Construction Production
26 Yaroslavskoe shosse, Moscow, 129337
Scopus: 57192378750
References
1. Bolodurina I.P., Speshilov E.A. Mathematical and instrumental means for providing an intelligent decision supрort system for managing cargo flows. Apрlied mathematics and management issues. 2023; 2:93-107. DOI: 10.15593/2499-9873/2023.2.09. EDN HILJFN. (rus.).
2. Lamekhov V., Chervotenko E. Usage of Dynamic Programming Method in Transport and Logistics Centers Construction and Development Projects. Advances in Intelligent Systems and Computing. In book: VIII International Scientific Siberian Transport Forum. 2020; 1115:357-366. DOI: 10.1007/978-3-030-37916-2_35
3. Dyukova O.M. Construction logistics: modern understanding and trends. Bulletin of URAO. 2017; 4:69-73. EDN OAGRQH. (rus.).
4. Karpushkin I.D. Current issues of construction logistics at the present stage. Fundamentals of EUP. 2023; 2(37):95-99. DOI: 10.51608/23058641_2023_2_95. EDN RQMEEP. (rus.).
5. Sedov D.S. Factors of constraint in conditions of dense urban development. Vestnik MGSU [Monthly Journal on Construction and Architecture]. 2010; 4(1):171-174. EDN NEJDSH.
6. Putz D., Schwabeneder D., Auer H., Fina B. A comparison between mixed-integer linear programming and dynamic programming with state prediction as novelty for solving unit commitment. International Journal of Electrical Power & Energy Systems. 2021; 125:3-12. DOI: 10.1016/j.ijepes.2020.106426
7. Mizutania E., Dreyfus S. A tutorial on the art of dynamic programming for some issues concerning Bellman’s principle of optimality. ICT Express. 2023; 9:1144-1161. DOI: 10.1016/j.icte.2023.07.001
8. Sun J., Apornak A., Ma G. Presenting a mathematical model for reduction of delays in construction projects considering quality management criteria in uncertainty conditions. Journal of Engineering Research. 2023. DOI: 10.1016/j.jer.2023.08.021
9. Kedir F., Hall M.D. Resource efficiency in industrialized housing construction e A systematic review of current performance and future opрortunities. Journal of Cleaner Production. 2021; 286:15. DOI: 10.1016/j.jclepro.2020.125443
10. Zhang Y. A survey of dynamic programming algorithms. Applied and Computational Engineering. 2024; 35(1):183-189. DOI: 10.54254/2755-2721/35/20230392
11. Khaled E., Hisham S. Dynamic Site Layout Planning Using Approximate Dynamic Programming. Journal of Computing in Civil Engineering. 2009; 23(2):119-127. DOI: 10.1061/(ASCE)0887-3801(2009)23:2(119)
12. Shramko A.P. Optimization of transport and technological processes using the dynamic programming method. Marine intellectual technologies. 2021; 4(1):184-194. DOI: 10.37220/MIT.2021.54.4.050. EDN UGPEGW. (rus.).
13. Basarab A. Application of dynamic programming in problems of managing professional risks in construction. Safety in the technosphere. 2017; 6(6):47-53. DOI: 10.12737/article_5af024e4e17da6.63463049. EDN XNBWQP. (rus.).
14. Pimenov S.I. Construction information model. Bulletin of PNIPU. Construction and architecture. 2022; 3(13):72-84. DOI: 10.15593/2224-9826/2022.3.07 (rus.).
15. Taghaddos M., Mousaei A., Taghaddos H., Hermann U., Mohamed Y., AbouRizk S. Optimized variable resource allocation framework for scheduling of fast-track industrial construction projects. Automation in Construction. 2024; 158:24. DOI: 10.1016/j.autcon.2023.105208
16. Essien J. Application of branch and bound and dynamic Programming in demand forecasting for supрly chain optimization. International Journal of Science and Research. 2023; 12 (5):2617-2623. DOI: 10.21275/SR23528175430
17. Shepelev V.D., Almetova Z.V., Shepeleva E.V., Alferova I.D. The use of shunting vehicles to reduce downtime at the turnover point. Bulletin of the South Ural State University. Series: Economics and management. 2018; 3:169-175. DOI: 10.14529/em180320. EDN YBJWQX. (rus.)
18. Ran Y. Optimizing Operations Management and Business Analytics Strategies under Uncertainty: Dynamic Programming. Advances in Economics Management and Political Sciences. 2023; 49(1):150-156. DOI: 10.54254/2754-1169/49/20230507
19. Louadj K., Aidene M. Direct Method for Resolution of Optimal Control Problem with Free Initial Condition. International Journal of Differential Equations. 2012; 6:18. DOI: 10.1155/2012/173634
20. Mamontova E.V., Voeyko O.A. Application of lean production in assessing the quality of waste management. Competence. 2024; 1:51-56. DOI: 10.24412/1993-8780-2024-1-51-57 (rus.).
21. Ilyuk V.V., Kuznetsov O.A. Increasing the efficiency of logistics flow management. RMAT Bulletin. 2023; 2:21-26. EDN WDCNDI. (rus.).
Review
For citations:
Ageeva Ya.D., Chirkunov Yu.A., Lapidus A.A. Planning of construction supply system in constrained conditions using the dynamic programming method. Vestnik MGSU. 2024;19(12):2001-2013. (In Russ.) https://doi.org/10.22227/1997-0935.2024.12.2001-2013