Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The paper introduces a new multi-factor critical chain buffer estimation model and designs a dynamic monitoring method based on the project elements. A literature analysis determined a research gap and a research problem. It was found that the existing methods offer scarce collaborative studies on buffer setting and monitoring and insufficient research on buffer setting considering project economic indicators. However, these topics are often given priority consideration in practical engineering applications. Therefore, the study proposes a multi-factor critical chain buffer setting and its dynamic monitoring method. The planning stage analyses the impact of income, resources, and probability of success on buffer size setting and defines the calculation model of capacity constraint buffer. The execution stage dynamically sets buffer monitoring points according to the progress of project implementation, monitors the remaining buffer amount at the completion of each activity on the critical chain, and takes corresponding actions to ensure that the progress is controllable. The method was applied in a multi-project of a Chinese software enterprise. To further verify the effectiveness of this research, the method is compared with the traditional static buffer monitoring method (TBMM) and the relative buffer monitoring method (RBMM), and the construction period of the real project is simulated through the computer program for analysis. Results show that the research method can reduce unreasonable buffer settings, enhance the robustness of a buffer against complex environments, and reduce the probability of false warnings in the monitoring process.
Rocznik
Tom
Strony
90--105
Opis fizyczny
Bibliogr. 29 poz., tab.
Twórcy
autor
- Shanghai Yangtze Delta Innovation Institute, 14-15 Yunfei Building, No. 257 Xiangke Road, Pudong New Area, Shanghai, China
autor
- College of Biomass Science and Engineering, Sichuan University, 24 South Section 1, 1st Ring Road, Chengdu, China
Bibliografia
- An, J., Li, S. C., & Wu, X. P. (2024). Multi-objective planning for time-cost trade-offs in multi-project parallel environment. Engineering Construction and Architectural Management, 32(6), 4051-4073. doi: 10.1108/ecam-08-2023-0867
- Bakry, I., Moselhi, O., & Zayed, T. (2016). Optimized scheduling and buffering of repetitive construction projects under uncertainty. Engineering Construction and Architectural Management, 23(6), 782-800. doi: 10.1108/ecam-05-2014-0069
- Bie, L., & Cui, N.. (2010). Research on dynamic buffer monitoring in critical chain project management. Chinese Journal of Management Science, 18(6), 97-103. doi: 10.16381/j.cnki.issn1003-207x.2010.06.003
- Bie, L., Cui, N. F., & Zhang, X. M. (2012). Buffer sizing approach with dependence assumption between activities in critical chain scheduling. International Journal of Production Research, 50(24), 7343-7356. doi: 10.1080/00207543.2011.649096
- Bie, L., Cui, N., & Tian, W. (2014). Research on activity sensitivity index based dynamic buffer monitoring method. Chinese Journal of Management Science, 22(10), 113-121. doi: 10.16381/j.cnki.issn1003207x.2014.10.005
- Bredael, D., & Vanhoucke, M. (2024). A genetic algorithm with resource buffers for the resource-constrained multi-project scheduling problem. European Journal of Operational Research, 315(2), 19-34. doi: 10.1016/j.ejor.2023.11.009
- Bu, Z., Liang, X., & Meng, H. (2021). Improved Method and Application of Critical Chain Identification Based on Multi-Project Important Degree. Industrial Engineering and Management, 26(5), 187-194. doi: 10.19495/j.cnki.1007-5429.2021.05.023
- Dalouchei, F., Mousavi, S. M., Antucheviciene, J., & Minaei, A. (2022). A Bi-Objective Model for Scheduling Construction Projects Using Critical Chain Method and Interval-Valued Fuzzy Sets. Buildings, 12(7), Article 904. doi: 10.3390/buildings12070904
- Ghoddousi, P., Ansari, R., & Makui, A. (2017). A RiskOriented Buffer Allocation Model Based on Critical Chain Project Management. Ksce Journal of Civil Engineering, 21(5), 1536-1548. doi: 10.1007/s12205016-0039-y
- Goudarzi, E., Esmaeeli, H., Parsa, K., & Asadzadeh, S. (2024). Energy-efficient resource-constrained multi-project scheduling problem with generalized precedence relations and multi-skilled resources. Journal of Supercomputing, 80(10), 13837-13872. doi: 10.1007/s11227-024-05933-0
- Hu, X. J., Demeulemeester, E., Cui, N. F., Wang, J. J., & Tian, W. D. (2017). Improved critical chain buffer management framework considering resource costs and schedule stability. Flexible Services and Manufacturing Journal, 29(2), 159-183. doi: 10.1007/s10696-0169241-y
- Kamandanipour, K., Tavakkoli-Moghaddam, R., & Yakhchali, S. H. (2023). A discrete time/resource trade-off problem with a critical chain method under uncertainty: a hybrid meta-heuristic algorithm. Soft Computing, 27(23), 17867-17885. doi: 10.1007/s00500023-09065-0
- Leach, L. P. (2005). Critical Chain Project Management. London, England: Artech House.
- Li, H. B., Cao, Y. W., Lin, Q., & Zhu, H. Y. (2022). Datadriven project buffer sizing in critical chains. Automation in Construction, 135, 104134. doi: 10.1016/j.autcon.2022.104134
- Luong Duc, L., & Ohsato, A. (2008). Fuzzy critical chain method for project scheduling under resource constraints and uncertainty. International Journal of Project Management, 26(6), 688-698. doi: 10.1016/j.ijproman.2007.09.012
- Mozhdehi, S., Baradaran, V., & Hosseinian, A. H. (2024). Multi-skilled resource-constrained multi-project scheduling problem with dexterity improvement of workforce. Automation in Construction, 162, 105360. doi: 10.1016/j.autcon.2024.105360
- Peng, J. L., & Peng, C. (2022). Buffer Sizing in Critical Chain Project Management by Brittle Risk Entropy. Buildings, 12(9), 1390. doi: 10.3390/buildings12091390
- Satic, U., Jacko, P., & Kirkbride, C. (2024). A simulationbased approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem. European Journal of Operational Research, 315(2), 454-469. doi: 10.1016/j.ejor.2023.10.046
- She, B. L., Chen, B., & Hall, N. G. (2021). Buffer sizing in critical chain project management by network decomposition *. Omega-International Journal of Management Science, 102, 102382. doi: 10.1016/j.omega.2020.102382
- Trietsch, D. (2005). The effect of systemic errors on optimal project buffers. International Journal of Project Management, 23(4), 267-274. doi: 10.1016/j.ijproman.2004.12.004
- Tukel, O. I., Rom, W. O., & Eksioglu, S. D. (2006). An investigation of buffer sizing techniques in critical chain scheduling. European Journal of Operational Research, 172(2), 401-416. doi: 10.1016/j.ejor.2004.10.019
- Zhang, J. G., & Han, Q. (2023a). Adaptive capacity constraint buffer monitoring of the multi-project system based on the relevance of drum activities. Kybernetes, 52(10), 4668-4685. doi: 10.1108/k-11-2021-1147
- Zhang, J. G., & Han, Q. (2023b). Buffer Monitoring of Critical Chain Projects Based on Support Vector Machine Prediction. Ksce Journal of Civil Engineering, 27(7), 2745-2755. doi: 10.1007/s12205-023-0033-0
- Zhang, J. G., Jia, S. K., & Diaz, E. (2018). Dynamic monitoring and control of a critical chain project based on phase buffer allocation. Journal of the Operational Research Society, 69(12), 1966-1977. doi: 10.1080/01605682.2017.1415641
- Zhang, J. G., Wan, D. (2018). Dynamic real-time monitoring and control of the critical chain project. Chinese Journal of Management Science, 26(4), 171-178. doi: 10.16381/j.cnki.issn1003-207x.2018.04.019
- Zhang, J. G., & Wan, D. (2019). Integrated buffer monitoring and control based on grey neural network. Journal of the Operational Research Society, 70(3), 516529. doi: 10.1080/01605682.2018.1447251
- Zhang, J. G., & Wang, M. H. (2022). Differential buffer monitoring for critical chain projects based on comprehensive activity reliability. Journal of the Operational Research Society, 74(9), 2064-2079. doi: 10.1080/01605682.2022.2125845
- Zhao, Y., Hu, X. J., Wang, J. J., & Cui, N. F. (2024). A robust multi-project scheduling problem under a resource dedication-transfer policy. Annals of Operations Research, 337(1), 425-457. doi: 10.1007/s10479-02405854-4
- Zhao, Y., Jing, H. T., Yu, M., & Li, J. M. (2024). Efficient project management of historical building groups: a BIM-based approach with critical chain method and 5D simulation. International Journal of Construction Management, 25(7), 826-839. doi: 10.1080/15623599.2024.2366711
Typ dokumentu
Bibliografia
Identyfikator YADDA
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