Graph-Based Automated Construction Scheduling without the Use of BIM
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 2
Abstract
The construction industry has been suffering from delays and cost overruns for decades. Experienced schedulers programs and allocate contingencies (both cost and time) based on professional experiences and gained knowledge. Such tacit knowledge has not been captured, stored, and shared with inexperienced schedulers. This paper proposes a graph-based automated scheduling (GAS) method to capture, store, and reuse the tacit knowledge in the construction schedules. The proposed GAS method takes construction schedules as input, extracts schedule features, classifies schedules into different types of sequences, selects and assembles sequences into schedules, and eventually optimizes time- and cost-efficiency of assembled schedules. The GAS method was validated on two case studies. The results indicated that the automatically generated construction schedule is, on average, 6.70% closer to the actual schedule than the planned schedule. Different from existing automatic scheduling methods, GAS relies little on the availability and data richness of building information modeling (BIM) models. Hence, GAS helps schedulers initiate new schedules more efficiently at the early construction stages.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies (https://doi.org/10.17863/CAM.53985).
Acknowledgments
We thank Kier for sharing experiences and knowledge in scheduling practice and using scheduling software, nPlan for sharing the data parsing prototype and valuable discussion about machine learning techniques, and Donn Ng for sharing the case study data. The presented work was based on research funded by InnovateUK (Project Reference 104795).
References
Addis, M. 2016. “Tacit and explicit knowledge in construction management.” Construct. Manage. Econ. 34 (7–8): 16. https://doi.org/10.1080/01446193.2016.1180416.
Al Nasseri, H., and R. Aulin. 2015. “Assessing understanding of planning and scheduling theory and practice on construction projects.” Eng. Manage. J. 27 (2): 58–72. https://doi.org/10.1080/10429247.2015.1035963.
Altun, M., and A. Akcamete. 2019. “A method for facilitating 4D modeling by automating task information generation and mapping.” In Advances in informatics and computing in civil and construction engineering, 479–486. Berlin: Springer.
Amer, F., and M. Golparvar-Fard. 2019. “Automatic understanding of construction schedules: Part-of-activity tagging.” In Proc., 2019 European Conf. on Computing in Construction, 190–197. Amsterdam, Netherlands: Elsevier.
Amer, F., and M. Golparvar-Fard. 2021. “Modeling dynamic construction work template from existing scheduling records via sequential machine learning.” Adv. Eng. Inf. 47 (Feb): 101198. https://doi.org/10.1016/j.aei.2020.101198.
Amer, F., Y. Jung, and M. Golparvar-Fard. 2021. “Transformer machine learning language model for auto-alignment of long-term and short-term plans in construction.” Autom. Constr. 132 (Dec): 103929. https://doi.org/10.1016/j.autcon.2021.103929.
Arditi, D., and S. N. Bentotage. 1996. “System for scheduling highway construction projects.” Comput.-Aided Civ. Infrastruct. Eng. 11 (2): 123–139. https://doi.org/10.1111/j.1467-8667.1996.tb00316.x.
Ballesteros-Pérez, P., M. L. Del Campo-Hitschfeld, M. A. González-Naranjo, and M. C. González-Cruz. 2015. “Climate and construction delays: Case study in Chile.” Eng. Constr. Archit. Manage. 22 (6): 596–621. https://doi.org/10.1108/ECAM-02-2015-0024.
Benjamin, C. O., D. L. Babcock, N. B. Yunus, and J. Kincaid. 1990. “Knowledge-based prototype for improving scheduling productivity.” J. Comput. Civ. Eng. 4 (2): 124–134. https://doi.org/10.1061/(ASCE)0887-3801(1990)4:2(124).
Changali, S., A. Mohammad, and M. van Nieuwland. 2015. “The construction productivity imperative.” Accessed February 16, 2020. https://www.mckinsey.com/business-functions/operations/our-insights/the-construction-productivity-imperative.
Cheng, M.-Y., Y.-H. Chang, and D. Korir. 2019. “Novel approach to estimating schedule to completion in construction projects using sequence and nonsequence learning.” J. Constr. Eng. Manage. 145 (11): 04019072. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001697.
Construction Industry Institute. n.d. “Best practices.” Accessed August 1, 2022. https://www.construction-institute.org/resources/knowledgebase/best-practices.
Crawford, M., and R. O’Leary. 1997. Uniclass: Unified classification for the construction industry. London: Royal Institute of British Architects.
Davis, R., A. Wilen, L. Bryer, D. Ward, F. Pottier, L. Cavin, S. Blofeld, and M. Blackwell. 2018. UK industry performance Report 2018. Bournemouth, UK: Glenigan.
de Snoo, C., W. van Wezel, and R. J. Jorna. 2011. “An empirical investigation of scheduling performance criteria.” J. Oper. Manage. 29 (3): 181–193. https://doi.org/10.1016/j.jom.2010.12.006.
Edvinsson, L. 1997. “Developing intellectual capital at Skandia.” Long Range Plann. 30 (3): 366–373. https://doi.org/10.1016/S0024-6301(97)90248-X.
El-Diraby, T. 2013. “Domain ontology for construction knowledge.” J. Constr. Eng. Manage. 139 (7): 768–784. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000646.
ElZomor, M., R. Burke, K. Parrish, and G. E. Gibson. 2018. “Front-end planning for large and small infrastructure projects: Comparison of project definition rating index tools.” J. Manage. Eng. 34 (4): 04018022. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000611.
Esmi, R., and R. Ennals. 2009. “Knowledge management in construction companies in the UK.” AI Soc. 24 (2): 197–203. https://doi.org/10.1007/s00146-009-0202-9.
Faghihi, V., K. F. Reinschmidt, and J. H. Kang. 2014. “Construction scheduling using genetic algorithm based on building information model.” Expert Syst. Appl. 41 (16): 7565–7578. https://doi.org/10.1016/j.eswa.2014.05.047.
Fang, Y., and S. T. Ng. 2019. “Genetic algorithm for determining the construction logistics of precast components.” Eng. Constr. Archit. Manage. 26 (10): 2289–2306. https://doi.org/10.1108/ECAM-09-2018-0386.
Fischer, M., F. Aalami, and M. O’Brien Evans. 1994. “Model-based constructibility analysis: The MOCA system.” In Proc., CIB W78 Workshop on Computer Integrated Construction. Slovenia: ITC Digital Library.
Fırat, C. E., J. Kiiras, and P. Huovinen. 2008. “A building construction information model for managing projects virtually.” Innov. Archit. Eng. Constr. 2008 (1): 23–25.
Fırat, C. E., J. Kiiras, K. Kähkönen, and P. Huovinen. 2007. “Model based scheduling in building projects–Is it oxymoron?” In Proc., 24th CIB W78 Conf. Slovenia: ITC Digital Library.
Flyvbjerg, B. 2007. “Policy and planning for large-infrastructure projects: Problems, causes, cures.” Environ. Plann. B: Plann. Des. 34 (4): 578–597. https://doi.org/10.1068/b32111.
Gibson, G., J. H. Kaczmarowski, and H. E. Lore, Jr. 1993. Modelling pre-project planning for the construction of capital facilities. Austin, TX: Univ. of Texas.
Gibson, G. E., K. T. Irons, and M. P. Ray. 2006. “Front end planning for buildings.” In Proc., 2006 Architectural Engineering National Conf. AEI 2006: Building Integration Solutions, 41. Reston, VA: ASCE.
Gondia, A., A. Siam, W. El-Dakhakhni, and A. H. Nassar. 2020. “Machine learning algorithms for construction projects delay risk prediction.” J. Constr. Eng. Manage. 146 (1): 04019085. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001736.
Goodarzizad, P., E. Mohammadi Golafshani, and M. Arashpour. 2021. “Predicting the construction labour productivity using artificial neural network and grasshopper optimisation algorithm.” Int. J. Constr. Manage. 2021 (1): 1–17. https://doi.org/10.1080/15623599.2021.1927363.
Hau, Y. S., B. Kim, H. Lee, and Y. G. Kim. 2013. “The effects of individual motivations and social capital on employees’ tacit and explicit knowledge sharing intentions.” Int. J. Inf. Manage. 33 (2): 356–366. https://doi.org/10.1016/j.ijinfomgt.2012.10.009.
He, W., Y. Shi, and D. Kong. 2019. “Construction of a 5D duration and cost optimisation model based on genetic algorithm and BIM.” J. Eng. Des. Technol. 17 (5): 929–942. https://doi.org/10.1108/JEDT-12-2018-0214.
Hong, Y., H. Xie, G. Bhumbra, and I. Brilakis. 2021. “Comparing natural language processing methods to cluster construction schedules.” J. Constr. Eng. Manage. 147 (10): 04021136. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002165.
Hong, Y., H. Xie, V. Hovhannisyan, and I. Brilakis. 2022. “A graph-based approach for unpacking construction sequence analysis to evaluate schedules.” Adv. Eng. Inf. 52 (4): 101625. https://doi.org/10.1016/j.aei.2022.101625.
Hutton, J. 2019. Cost overruns of major government projects. Reston, VA: ASCE.
Kartam, N. A., and R. E. Levitt. 1990. “Intelligent planning of construction projects.” J. Comput. Civ. Eng. 4 (2): 155–176. https://doi.org/10.1061/(ASCE)0887-3801(1990)4:2(155).
Kolodner, J. L. 1992. “An introduction to case-based reasoning.” Artif. Intell. Rev. 6 (1): 3–34. https://doi.org/10.1007/BF00155578.
Kyungki, K., W. John, and Y. K. Cho. 2016. “Multiobjective construction schedule optimization using modified niched Pareto genetic algorithm.” J. Manage. Eng. 32 (2): 4015038. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000374.
Li, Y., K. Lu, and Y. Lu. 2017. “Project schedule forecasting for skyscrapers.” J. Manage. Eng. 33 (3): 05016023. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000498.
Liu, H., M. Al-Hussein, and M. Lu. 2015. “BIM-based integrated approach for detailed construction scheduling under resource constraints.” Autom. Constr. 53 (May): 29–43. https://doi.org/10.1016/j.autcon.2015.03.008.
Lu, W., and T. Olofsson. 2014. “Building information modeling and discrete event simulation: Towards an integrated framework.” Autom. Constr. 44 (Aug): 73–83. https://doi.org/10.1016/j.autcon.2014.04.001.
Mitchell, M. 1995. “Genetic algorithms: An overview.” In Complex, 31–39. Princeton, NJ: Citeseer.
Mitchell, M. 1996. An introduction to genetic algorithms. Cambridge, MA: MIT Press.
Morkos, R. 2014. Operational efficiency frontier: Visualizing, manipulating, and navigating the construction scheduling state space with precedence, discrete, and disjunctive constraints. Stanford, CA: Stanford Univ.
Muñoz-Avila, H., D. W. Aha, D. S. Nau, R. Weber, L. Breslow, and F. Yaman. 2001. SiN: Integrating case-based reasoning with task decomposition. Seattle: Maryland Univ.
Naticchia, B., A. Carbonari, M. Vaccarini, and R. Giorgi. 2019. “Holonic execution system for real-time construction management.” Autom. Constr. 104 (Apr): 179–196. https://doi.org/10.1016/j.autcon.2019.04.018.
Park, H.-S., S. R. Thomas, and R. L. Tucker. 2005. “Benchmarking of construction productivity.” J. Constr. Eng. Manage. 131 (7): 772–778. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:7(772).
Park, J., and H. Cai. 2017. “WBS-based dynamic multi-dimensional BIM database for total construction as-built documentation.” Autom. Constr. 77 (Jan): 15–23. https://doi.org/10.1016/j.autcon.2017.01.021.
Paul, J. C., D. Gertsch, and L. Pytel. 1992. “Graffiti: A computer-aided construction process knowledge-based system.” Comput.-Aided Civ. Infrastruct. Eng. 7 (1): 81–88. https://doi.org/10.1111/j.1467-8667.1992.tb00419.x.
Petroutsatou, K., and P. Giannoulis. 2020. “Analysis of construction machinery market: The case of Greece.” Int. J. Constr. Manage. 22 (9): 1667–1674. https://doi.org/10.1080/15623599.2020.1741491.
Royal Institution of Charted Surveyors. 1988. SMM7—A code of procedure for measurement of building works. London: Royal Institution of Chartered Surveyors.
Salesky, M. E. 2017. The project managers guide to IDIQ task order service contracts. Cham, Switzerland: Springer Nature.
Shen, L. Y. 1997. “Project risk management in Hong Kong.” Int. J. Project Manage. 15 (2): 101–105. https://doi.org/10.1016/S0263-7863(96)00045-2.
Shrestha, P. P., and R. Maharjan. 2018. “Effects of change orders on cost growth, schedule growth, and construction intensity of large highway projects.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 10 (3): 04518012. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000264.
Singh, J., J. C. P. Cheng, and C. J. Anumba. 2021. “BIM-Based approach for automatic pipe systems installation coordination and schedule optimization.” J. Constr. Eng. Manage. 147 (11): 04021143. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002077.
Tauscher, E., E. Mikulakova, K. Beucke, and M. König. 2009. “Automated generation of construction schedules based on the IFC object model.” In Proc., 2009 ASCE Int. Workshop on Computing in Civil Engineering. Reston, VA: ASCE.
Torres-Calderon, W., Y. Chi, F. Amer, and M. Golparvar-Fard. 2019. “Automated mining of construction schedules for easy and quick assembly of 4D BIM simulations.” In Proc., ASCE Int. Conf. on Computing in Civil Engineering 2019. Reston, VA: ASCE.
Wang, Z., and E. Rezazadeh Azar. 2019. “BIM-based draft schedule generation in reinforced concrete-framed buildings.” Constr. Innov. 19 (2): 280–294. https://doi.org/10.1108/CI-11-2018-0094.
Westney, R. E. 1997. The Engineer’s cost handbook: Tools for managing project costs. Boca Raton, FL: CRC Press.
Wu, I.-C., A. Borrmann, U. Beißert, M. König, and E. Rank. 2010. “Bridge construction schedule generation with pattern-based construction methods and constraint-based simulation.” Adv. Eng. Inf. 24 (4): 379–388. https://doi.org/10.1016/j.aei.2010.07.002.
Xu, K., and H. Muñoz-Avila. 2008. “CaBMA: A case-based reasoning system for capturing, refining, and reusing project plans.” Knowledge Inf. Syst. 15 (2): 215–232. https://doi.org/10.1007/s10115-007-0077-3.
Zayed, T. M., and D. W. Halpin. 2005. “Pile construction productivity assessment.” J. Constr. Eng. Manage. 131 (6): 705–714. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:6(705).
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 2 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: May 11, 2022
Accepted: Sep 15, 2022
Published online: Dec 14, 2022
Published in print: Feb 1, 2023
Discussion open until: May 14, 2023
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.