Journal of Structural and Construction Engineering

Journal of Structural and Construction Engineering

Solving multi-project scheduling problem under resource constraints (RCMPSP): an approach based on building information modeling

Document Type : Original Article

Authors
Mohammad Sajjad Moradnia 1
Yaghoub Alipouri 2
1 Graduated student, Construction engineering and management, Construction Engineering and Management Department, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 Assistant Professor, Department of Construction Engineering and Management, Faculty of Civil Engineering, K. N. Toosi University of Technology, Tehran, Iran.
10.22065/jsce.2025.490336.3582
Abstract
Solving the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) is one of the most complex challenges in project management. This complexity arises from resource limitations and precedence relationships among project activities. When an organization manages multiple construction projects simultaneously, efficient scheduling is essential for on-time completion and optimal resource utilization. In recent decades, Building Information Modeling (BIM) has played a significant role in advancing the construction industry by providing a powerful framework for planning, design, and project management. However, BIM has not yet been fully leveraged to address the complexities of RCMPSP. This research presents an innovative approach to solving RCMPSP by enabling the use of BIM for multi-project scheduling under resource constraints, thereby helping to reduce delays and costs. First, the necessary data for solving the problem is extracted from a detailed Building Information Model using Autodesk Navisworks Manage software. This model records all relevant information about project phases, resource requirements, and activity dependencies. Next, the extracted data is processed using a Particle Swarm Optimization (PSO) algorithm implemented in Matlab. The PSO algorithm is well-suited for this problem due to its ability to search the solution space and identify near-optimal solutions within a short time frame. Finally, to simulate the construction process, the optimized schedule is transferred to the TimeLiner tool in Navisworks Manage via an API developed in C# using Visual Studio. This integration enables real-time simulation and analysis of the construction process. The proposed approach was evaluated using data from a hypothetical project, and the results demonstrated its effectiveness in solving RCMPSP. Adopting this approach can improve time management and resource allocation in construction companies, leading to significant cost savings and increased efficiency in project execution.
Keywords
Resource-constrained multi-project scheduling problem (RCMPSP)
Building information modeling (BIM)
Particle swarm optimization (PSO) algorithm
Application programming interface (API)
TimeLiner tool

Subjects

[1]        V. Faghihi, K. F. Reinschmidt, and J. H. Kang,  (2014 )"Construction scheduling using genetic algorithm based on building information model," Expert Systems with Applications, vol. 41, no. 16, pp. 7565-7578. https://doi.org/10.1016/j.eswa.2014.05.047
[2]        A. Kastor and K. Sirakoulis, (2009) "The effectiveness of resource levelling tools for resource constraint project scheduling problem," International Journal of Project Management, vol. 27, no. 5, pp. 493-500. https://doi.org/10.1016/j.ijproman.2008.08.006
[3]        L. Özdamar and G. Ulusoy, (1995)."A survey on the resource-constrained project scheduling problem," IIE transactions, vol. 27, no. 5, pp. 574-586 . https://doi.org/10.1080/07408179508936773
[4]        J. Blazewicz, J. K. Lenstra, and A. R. Kan, (1983) "Scheduling subject to resource constraints: classification and complexity," Discrete applied mathematics, vol. 5, no. 1, pp. 11-24. https://doi.org/10.1016/0166-218X(83)90012-4
[5]        F. Kong and D. Dou, (2021) "Resource-constrained project scheduling problem under multiple time constraints," Journal of Construction Engineering and Management, vol. 147, no. 2, p. 04020170. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001990
[6]        T. R. Browning and A. A. Yassine, (2010) "A random generator of resource-constrained multi-project network problems," Journal of scheduling, vol. 13, pp. 143-161. https://doi.org/10.1007/s10951-009-0131-y
[7]        S. Hartmann and D. Briskorn, (2022) "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of operational research, vol. 297, no. 1, pp. 1-14. https://doi.org/10.1016/j.ejor.2021.05.004
[8]        M. G. Sánchez, E. Lalla-Ruiz, A. F. Gil, C. Castro, and S. Voß, (2023) "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, vol. 309, no. 3, pp. 958-976. https://doi.org/10.1016/j.ejor.2022.09.033
[9]        H. Liu, M. Al-Hussein, and M. Lu, (2015)"BIM-based integrated approach for detailed construction scheduling under resource constraints," Automation in Construction, vol. 53, pp. 29-43. https://doi.org/10.1016/j.autcon.2015.03.008
[10]      J. Tulke and J. Hanff, (2007) "4D construction sequence planning–new process and data model," in Proceedings of CIB-W78 24th International Conference on Information Technology in Construction, Maribor, Slovenia, pp. 79-84. https://itc.scix.net/pdfs/w78-2007-012-088-Tulke.pdf
[11]      H. Kim, K. Anderson, S. Lee, and J. Hildreth, (2013) "Generating construction schedules through automatic data extraction using open BIM (building information modeling) technology," Automation in Construction, vol. 35, pp. 285-295, 2. https://doi.org/10.1016/j.autcon.2013.05.020
[12]      S. S. Martins, A. C. J. Evangelista, A. W. Hammad, V. W. Tam, and A. Haddad, (2022) "Evaluation of 4D BIM tools applicability in construction planning efficiency," International Journal of Construction Management, vol. 22, no. 15, pp. 2987-3000. https://doi.org/10.1080/15623599.2020.1837718
[13]      W.-C. Wang, S.-W. Weng, S.-H. Wang, and C.-Y. Chen, (2014) "Integrating building information models with construction process simulations for project scheduling support," Automation in construction, vol. 37, pp. 68-80. https://doi.org/10.1016/j.autcon.2013.10.009
[14]      K. Sigalov and M. König, (2017) "Recognition of process patterns for BIM-based construction schedules," Advanced Engineering Informatics, vol. 33, pp. 456-472. https://doi.org/10.1016/j.aei.2016.12.003
[15]      J. Crowther and S. O. Ajayi, (2021) "Impacts of 4D BIM on construction project performance," International Journal of Construction Management, vol. 21, no. 7, pp. 724-737. https://doi.org/10.1080/15623599.2019.1580832
[16]      R. Torba, S. Dauzère-Pérès, C. Yugma, C. Gallais, and J. Pouzet,(2024) "Solving a real-life multi-skill resource-constrained multi-project scheduling problem," Annals of Operations Research, pp. 1-46. https://doi.org/10.1007/s10479-023-05784-7
[17]      S. Xin, Q. Su, Q. Wang, and Q. Wang,(2015) "Optimization of resource-constrained multi-project scheduling problem based on the genetic algorithm," 15th International conference on service systems and service management (ICSSSM), 2018, pp. 1-6: IEEE. https://doi.org/10.1109/ICSSSM.2018.8465086
[18]      D. Linyi and L. Yan, (2007) "A particle swarm optimization for resource-constrained multi-project scheduling problem," in 2007 International conference on computational intelligence and security (CIS 2007), pp. 1010-1014: IEEE. https://doi.org/10.1109/CIS.2007.157
[19]      N. Zoraghi, A. Shahsavar, B. Abbasi, and V. Van Peteghem, (2017) "Multi-mode resource-constrained project scheduling problem with material ordering under bonus–penalty policies," Top, vol. 25, pp. 49-79. https://doi.org/10.1007/s11750-016-0415-2
[20]      D. Liu, Z. Xu, and F. Li, (2019) "Distributed resource constrained multi-project scheduling problem with cooperative-game based negotiation mechanism," Syst. Eng.-Theory Pract, vol. 39, no. 6, pp. 1507-1516.
[21]      R. K. Chakrabortty, R. A. Sarker, and D. L. Essam, (2017) "Resource constrained multi-project scheduling: A priority rule based evolutionary local search approach," in Intelligent and Evolutionary Systems: The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, pp. 75-86: Springer. https://doi.org/10.1007/978-3-319-49049-6_6
[22]      L. Zhang and R. Sun, (2011) "An improvement of resource-constrained multi-project scheduling model based on priority-rule based heuristics," in ICSSSM11, pp. 1-5: IEEE. https://doi.org/10.1109/ICSSSM.2011.5959321
[23]      H. Zhang, H. Li, and C. Tam, (2006) "Heuristic scheduling of resource‐constrained, multiple‐mode and repetitive projects," Construction management and economics, vol. 24, no. 2, pp. 159-169. https://doi.org/10.1080/01446190500184311
[24]      A. Fazeli, S. Banihashemi, A. Hajirasouli, and S. R. Mohandes,(2024) "Automated 4D BIM development: The resource specification and optimization approach," Engineering, Construction and Architectural Management, vol. 31, no. 5, pp. 1896-1922. https://doi.org/10.1108/ECAM-07-2022-0665
[25]      H. Hamledari, B. McCabe, S. Davari, and A. Shahi, (2017) "Automated schedule and progress updating of IFC-based 4D BIMs," Journal of Computing in Civil Engineering, vol. 31, no. 4, p. 04017012. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000660
[26]      X. Jiang, (2011) "Developments in cost estimating and scheduling in BIM technology," Northeastern University. https://www.proquest.com/openview/a8dc41f96a6107e652b09b075ce58400/1?pq-origsite=gscholar&cbl=18750
[27]      J. Park and H. Cai, (2015) "Automatic construction schedule generation method through BIM model creation," in Computing in Civil Engineering 2015, pp. 620-627. https://doi.org/10.1061/9780784479247.077
[28]      E. Tauscher, K. Smarsly, M. König, and K. Beucke, (2014) "Automated generation of construction sequences using building information models," in Computing in Civil and Building Engineering, pp. 745-752. https://doi.org/10.1061/9780784413616.093
[29]      H. Liu, Z. Lei, H. X. Li, and M. Al-Hussein, (2014)"An automatic scheduling approach: building information modeling-based onsite scheduling for panelized construction," in Construction Research Congress 2014: Construction in a Global Network, pp. 1666-1675. https://doi.org/10.1061/9780784413517.170
[30]      R. Volk, T. H. Luu, J. S. Mueller-Roemer, N. Sevilmis, and F. Schultmann, (2018) "Deconstruction project planning of existing buildings based on automated acquisition and reconstruction of building information," Automation in construction, vol. 91, pp. 226-245. https://doi.org/10.1016/j.autcon.2018.03.017
[31]      R. Volk, N. Sevilmis, and F. Schultmann, (2015) "Deconstruction project planning based on automatic acquisition and reconstruction of building information for existing buildings,". https://publica.fraunhofer.de/entities/publication/71171bf4-f6eb-44a4-87e2-3213bc326af2
[32]      C. Chen and L. Tang,(2019) "BIM-based integrated management workflow design for schedule and cost planning of building fabric maintenance," Automation in construction, vol. 107, p. 102944. https://doi.org/10.1016/j.autcon.2019.102944
[33]      W. Chen, K. Chen, J. C. Cheng, Q. Wang, and V. J. Gan, (2018) "BIM-based framework for automatic scheduling of facility maintenance work orders," Automation in construction, vol. 91, pp. 15-30.  https://doi.org/10.1016/j.autcon.2018.03.007
[34]      K.-C. Wang, W.-C. Wang, H.-H. Wang, P.-Y. Hsu, W.-H. Wu, and C.-J. Kung, (2016) "Applying building information modeling to integrate schedule and cost for establishing construction progress curves," Automation in construction, vol. 72, pp. 397-410. https://doi.org/10.1016/j.autcon.2016.10.005
[35]      R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in MHS'95. Proceedings of the sixth international symposium on micro machine and human science, 1995, pp. 39-43: Ieee. https://doi.org/10.1109/MHS.1995.494215
[36]      M. Khalilzadeh, F. Kianfar, A. Shirzadeh Chaleshtari, S. Shadrokh, and M. Ranjbar,(2012) "A modified PSO algorithm for minimizing the total costs of resources in MRCPSP," Mathematical Problems in Engineering, vol. 2012. https://doi.org/10.1155/2012/365697
[37]      S. Asta, D. Karapetyan, A. Kheiri, E. Özcan, and A. J. Parkes, (2016)"Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem," Information Sciences, vol. 373, pp. 476-498. https://doi.org/10.1016/j.ins.2016.09.010

  • Receive Date 02 December 2024
  • Revise Date 05 January 2025
  • Accept Date 02 February 2025