English
Język Polski
Prognozowanie przebiegu przedsięwzięć budowlanych w warunkach niepewności
DOI:
https://doi.org/10.24425/ace.2023.146097Abstrakt
Metodyka i wyniki badań zaprezentowane w artykule wskazują na praktyczną możliwość optymalizacji kosztowej przebiegu przedsięwzięć budowlanych. Cel osiągnięcia prowadzi do racjonalizacji zarządzania zadań inwestycyjnych, w których występują sparametryzowane przeze mnie serie zdarzeń niepewnych. Cel został osiągnięty na drodze kilkunastoletnich badań własnych, które są prowadzone na kilkuset obiektach i budowach według autorskiej metodyki oceny i prognozy ich charakterystycznych parametrów (koszt i czas) w warunkach niepewności: od determinizmu, poprzez probabilistykę i przypadkowość, aż do rozmytości. Zarządzanie przedsięwzięciami budowlanymi i podejmowanie decyzji zarządczych następuje w rosnącym stopniu niepewności i wymaga prognozowania przebiegu zadań inwestycyjnych, które zostaną zrealizowane w przyszłości. W prezentowanych badaniach udowodniono, że procesy budowalne powinny być rozważane jako zjawiska ze zdarzeniami losowymi o różnym stopniu niepewności, do których stosować metodykę o zbliżonych parametrach modelowania.Bibliografia
[1] J. Konior, “Monitoring of construction projects feasibility by Bank Investment Supervision Approach”, Civil Engineering and Architecture, vol. 7, no. 1, pp. 31-35, 2019, doi: 10.13189/cea.2019.070105.
[2] J. Konior, “Feasibility study of construction project in compliance with Bank Investment Supervision requirements”, Journal of Civil Engineering and Architecture, vol. 12, pp. 831-837, 218, doi: 10.17265/1934-7359/2018.12.001.
[3] J. Konior, “Determining cost and time performance indexes for diversified investment tasks”, Buildings, vol. 12, no. 8, 2022, doi: 10.3390/buildings12081198.
[4] J. Konior and M. Szóstak, “Methodology of planning the course of the cumulative cost curve in construction projects”, Sustainability, vol. 12, no. 6, 2020, doi: 10.3390/SU12062347.
[5] J. Konior and M. Szóstak, “The S-curve as a tool for planning and controlling of construction process-case study”, Applied Sciences, vol. 10, no. 6, 2020, doi: 10.3390/app10062071.
[6] J. Konior, “Random and fuzzy measure of unpredictable construction works”, Archives of Civil Engineering, vol. 61, no. 3, pp. 75-84, 2015, doi: 10.1515/ace-2015-0026.
[7] J. Konior, “Fuzziness over randomness in unforeseen works of construction projects”, Civil Engineering and Architecture, vol. 7, no. 2, pp. 42-48, 2019, doi: 10.13189/cea.2019.070202.
[8] J. Konior, “Enterprise’s risk assessment of complex construction projects”, Archives of Civil Engineering, vol. 61, no. 3, pp. 63-74, 2016, doi: 10.1515/ace-2015-0025.
[9] J. Konior, “Mitigation of correlated risk in construction projects”, Civil Engineering and Architecture, vol. 7, no. 1, pp. 17-22, 2019, doi: 10.13189/cea.2019.070103.
[10] J. Konior, “Significance risks evaluation of commercial construction projects”, Archives of Civil Engineering, vol. 65, no. 2, pp. 19-33, 2019, doi: 10.2478/ace-2019-0016.
[11] S. Al-Jibouri, “Monitoring systems and their effectiveness for project cost control in construction”, International Journal of Project Management, vol. 21, pp. 145-154, 2003.
[12] S. Gardezi, I. Manarvi, and S. Gardezi, “Time extension factors in construction industry of Pakistan”, Procedia Engineering, vol. 77, pp. 196-204, 2014, doi: 10.1016/j.proeng.2014.07.022.
[13] S. Makesh and M. Mathivanan, “Analysis on causes of delay in building construction”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 7, pp. 335-341, 2019.
[14] T. Gebrehiwet and H. Luo, “Analysis of delay impact on construction project based on RII and correlation coefficient: empirical study”, Procedia Engineering, vol. 196, pp. 366-374, 2017, doi: 10.1016/j.proeng.2017.07.212.
[15] G. Barraza, W. Back, and F. Mata, “Probabilistic forecasting of project performance using stochastic Scurves”, Journal of Construction Engineering and Management, vol. 130, no. 1, pp. 25-32, 2004, doi: 10.1061/(ASCE) 0733-9364(2004)130:1(25).
[16] J. Yao, M. Chen, and H. Lu, “A fuzzy stochastic single-period model for cash management”, European Journal of Operational Research, vol. 170, no. 1, pp. 72-90, 2006, doi: 10.1016/j.ejor.2004.06.017.
[17] V. Kumar, A. Hanna, and T. Adams, “Assessment of working capital requirements by fuzzy set theory”, Engineering, Construction and Architectural Management, vol. 7, pp. 93-103, 2000.
[18] M. Cheng and A. Roy, “Evolutionary fuzzy decision model for cash flow prediction using time-dependent support vector machines”, International Journal of Project Management, vol. 29, no. 1, pp. 56-65, 2011, doi: 10.1016/j.ijproman.2010.01.004.
[19] M. Cheng, H. Tsai, and C. Liu, “Artificial intelligence approaches to achieve strategic control over project cash flows”, Automation in Construction, vol. 18, no. 4, pp. 386-393, 2009, doi: 10.1016/j.autcon.2008.10.005.
[20] A. Leśniak and K. Zima, “Cost calculation of construction projects including sustainability factors using the case based reasoning (CBR) method”, Sustainability, vol. 10, no. 5, 2018, doi: 10.3390/su10051608.
[21] T. Kasprowicz, “Quantitative assessment of construction risk”, Archives of Civil Engineering, vol. 63, no. 2, pp. 55-62, 2017, doi: 10.1515/ace-2017-0016.
[22] T. Kasprowicz, “Quantitative identification of construction risk”, Archives of Civil Engineering, vol. 63, no. 1, pp. 63-75, 2017, doi: 10.1515/ace-2017-0005.
[23] J. Cristóbal, “The S-curve envelope as a tool for monitoring and control of projects”, Procedia Computer Science, vol. 121, pp. 756-761, 2017, doi: 10.1016/J.PROCS.2017.11.097.
[24] N. Ibadov, “Fuzzy estimation of Activities Duration in Construction Projects”, Archives of Civil Engineering, vol. 61, no. 2, pp. 23-34, 2015, doi: 10.1515/ace-2015-0012.
[25] N. Ibadov, “The alternative net model with the fuzzy decision node for the construction projects planning”, Archives of Civil Engineering, vol. 64, no. 2, pp. 3-20, 2018, doi: 10.2478/ace-2018-0013.
[26] N. Ibadov and J. Kulejewski, “Construction projects planning using network model with the fuzzy decision node”, International Journal of Environmental Science and Technology, vol. 16, no. 8, pp. 4347-4354, 2019, doi: 10.1007/s13762-019-02259-w.
[27] N. Ibadov and J. Kulejewski, “The assessment of construction project risks with the use of fuzzy sets theory”, Technical Transactions, vol. 1-B, pp.175-182, 2014.
[28] S. Vandevoorde and M. Vanhoucke, “A comparison of different project duration forecasting methods using earned value metrics”, International Journal of Project Management, vol. 24, no. 4, pp. 289-302, 2006, doi: 10.1016/j.ijproman.2005.10.004.
[29] M. Vanhoucke and S. Vandevoorde, “A simulation and evaluation of earned value metrics to forecast the project duration”, Journal of the Operational Research Society, vol. 58, no. 10, pp. 1361-1374, 2007, doi: 10.1057/palgrave.jors.2602296.
[30] M. Khamidi, W. Ali, and A. Idrus, “Application of earned value management system on an infrastructure project : A Malaysian case study”, International Conference on Management Science & Engineering, vol. 8, pp. 1-5, 2011.
[31] O. Kwon, S. Kim, J. Paek, and S. Eom “Application of earned value in the Korean construction industry”, Journal of Asian Architecture and Building Engineering, vol. 7, pp. 69-76, 2008.
[32] M. Połoński and P. Komendarek, “Earned value method for operational cost control of civil structure”, Metody Ilościowe w Badaniach Ekonomicznych, vol. 12, pp. 279-290, 2011.
[33] E. Kozień “Application of approximation technique to on-line updating of the actual cost curve in the earned value method”, Czasopismo Techniczne, vol. 9, pp. 181-195, 2017, doi: 10.4467/2353737XCT.17.158.7170.
[34] A. Leśniak, D. Kubek, E. Plebankiewicz, K. Zima, and S. Belniak, “Fuzzy AHP application for supporting contractors’ bidding decision”, Symmetry, vol. 10, no. 11, art. no. 642, 2018, doi: 10.3390/sym10110642.
[35] A. Leśniak and E. Plebankiewicz, “Modeling the decision-making process concerning participation in construction bidding”, Journal of Management in Engineering, vol. 31, no. 2, 2015, doi: 10.1061/(ASCE)ME.1943-5479.0000237.
[36] J. Konior and M. Szóstak, “Course of planned, actual and earned cost curves of diverse construction investments”, International Journal of Construction Management, vol. 23, no. 5, pp. 1-13, 2023, doi: 10.1080/15623599.2021.1942769.
[37] M. Szóstak, “Planning the time and cost of implementing construction projects using an example of residential buildings”, Archives of Civil Engineering, vol. 67, no. 4, pp. 243-259, 2021, doi: 10.24425/ace.2021.138497.
Pobrania
Opublikowane
Jak cytować
Numer
Dział
