IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i13p2087-d1428238.html
   My bibliography  Save this article

Artificial Bee Colony Algorithm to Optimize the Safety Distance of Workers in Construction Projects

Author

Listed:
  • Eric Forcael

    (College of Engineering, Architecture, and Design, Universidad San Sebastián, Concepción 4081339, Chile)

  • Ibzan Carriel

    (Department of Civil and Environmental Engineering, College of Engineering, Universidad del Bío-Bío, Concepción 4051381, Chile)

  • Alexander Opazo-Vega

    (Department of Civil and Environmental Engineering, College of Engineering, Universidad del Bío-Bío, Concepción 4051381, Chile)

  • Francisco Moreno

    (College of Engineering, Universidad Panamericana, Guadalajara 45010, Mexico)

  • Francisco Orozco

    (College of Engineering, Universidad Panamericana, Guadalajara 45010, Mexico)

  • Rubén Romo

    (College of Engineering, Universidad Panamericana, Guadalajara 45010, Mexico)

  • Duzgun Agdas

    (Engineering School of Sustainable Infrastructure and Environment, University of Florida, Gainesville, FL 32611, USA)

Abstract

This paper presents the results of a simulation model regarding the productivity and safety working space for construction workers through the floors of a building using swarm intelligence (SI), a field of artificial intelligence (AI), and specifically using artificial bee colony (ABC) optimization. After designing the algorithm used to build the simulation model, the simulation was used in an actual building project by comparing the travel times of workers conventionally transporting material with another group working on routes optimized by the algorithm. Thus, the proposed algorithm provides routes combining shorter travel times and correct distances between workers when transporting materials in a construction site, handling the interference between crews. After validating the algorithm on-site, no statistically significant differences were found between the travel times of workers and the times delivered by the algorithm. Additionally, the travel times using the routes obtained through the algorithm were significantly lower than those made by workers who moved freely without a predefined route. In summary, the algorithm proposed may help construction practitioners maintain safe movements that respond to hazard contexts imposed by any restriction that demands a safety distance.

Suggested Citation

  • Eric Forcael & Ibzan Carriel & Alexander Opazo-Vega & Francisco Moreno & Francisco Orozco & Rubén Romo & Duzgun Agdas, 2024. "Artificial Bee Colony Algorithm to Optimize the Safety Distance of Workers in Construction Projects," Mathematics, MDPI, vol. 12(13), pages 1-23, July.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2087-:d:1428238
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/13/2087/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/13/2087/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrick Jaillet & Jin Qi & Melvyn Sim, 2016. "Routing Optimization Under Uncertainty," Operations Research, INFORMS, vol. 64(1), pages 186-200, February.
    2. Abdullah Alsharef & Siddharth Banerjee & S M Jamil Uddin & Alex Albert & Edward Jaselskis, 2021. "Early Impacts of the COVID-19 Pandemic on the United States Construction Industry," IJERPH, MDPI, vol. 18(4), pages 1-20, February.
    3. Pamela C. Nolz, 2021. "Optimizing construction schedules and material deliveries in city logistics: a case study from the building industry," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 846-878, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenlu Zhao & Guanghu Jin & Chenyue Huang & Jinji Zhang, 2023. "Attention and Sentiment of the Chinese Public toward a 3D Greening System Based on Sina Weibo," IJERPH, MDPI, vol. 20(5), pages 1-20, February.
    2. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    3. Qingyuan Luo & Peng Zhang & Yijia Liu & Xiujie Ma & George Jennings, 2022. "Intervention of Physical Activity for University Students with Anxiety and Depression during the COVID-19 Pandemic Prevention and Control Period: A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    4. Enrico Bartolini & Dominik Goeke & Michael Schneider & Mengdie Ye, 2021. "The Robust Traveling Salesman Problem with Time Windows Under Knapsack-Constrained Travel Time Uncertainty," Transportation Science, INFORMS, vol. 55(2), pages 371-394, March.
    5. Dimitris Bertsimas & Arthur Delarue & Patrick Jaillet & Sébastien Martin, 2019. "Travel Time Estimation in the Age of Big Data," Operations Research, INFORMS, vol. 67(2), pages 498-515, March.
    6. Timothy M. Sweda & Irina S. Dolinskaya & Diego Klabjan, 2017. "Adaptive Routing and Recharging Policies for Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1326-1348, November.
    7. Zhang, Yu & Wang, Yu & Tang, Jiafu & Lim, Andrew, 2020. "Mitigating overtime risk in tactical surgical scheduling," Omega, Elsevier, vol. 93(C).
    8. Zhao, Lei & Bi, Xinhua & Li, Gendao & Dong, Zhaohui & Xiao, Ni & Zhao, Anni, 2022. "Robust traveling salesman problem with multiple drones: Parcel delivery under uncertain navigation environments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    9. Longsheng Sun & Mark H. Karwan & Changhyun Kwon, 2018. "Generalized Bounded Rationality and Robust Multicommodity Network Design," Operations Research, INFORMS, vol. 66(1), pages 42-57, 1-2.
    10. Shubhechyya Ghosal & Wolfram Wiesemann, 2020. "The Distributionally Robust Chance-Constrained Vehicle Routing Problem," Operations Research, INFORMS, vol. 68(3), pages 716-732, May.
    11. Hossein Hashemi Doulabi & Gilles Pesant & Louis-Martin Rousseau, 2020. "Vehicle Routing Problems with Synchronized Visits and Stochastic Travel and Service Times: Applications in Healthcare," Transportation Science, INFORMS, vol. 54(4), pages 1053-1072, July.
    12. An Cheng & Tonghui Chen & Guogang Jiang & Xinru Han, 2021. "Can Major Public Health Emergencies Affect Changes in International Oil Prices?," IJERPH, MDPI, vol. 18(24), pages 1-13, December.
    13. Maaike Hoogeboom & Yossiri Adulyasak & Wout Dullaert & Patrick Jaillet, 2021. "The Robust Vehicle Routing Problem with Time Window Assignments," Transportation Science, INFORMS, vol. 55(2), pages 395-413, March.
    14. Arthur Flajolet & Sébastien Blandin & Patrick Jaillet, 2018. "Robust Adaptive Routing Under Uncertainty," Operations Research, INFORMS, vol. 66(1), pages 210-229, January.
    15. Zweers, Bernard G. & van der Mei, Rob D., 2022. "Minimum costs paths in intermodal transportation networks with stochastic travel times and overbookings," European Journal of Operational Research, Elsevier, vol. 300(1), pages 178-188.
    16. Sheng Liu & Long He & Zuo-Jun Max Shen, 2021. "On-Time Last-Mile Delivery: Order Assignment with Travel-Time Predictors," Management Science, INFORMS, vol. 67(7), pages 4095-4119, July.
    17. Qinghe Sun & Li Chen & Mabel C. Chou & Qiang Meng, 2023. "Mitigating the financial risk behind emission cap compliance: A case in maritime transportation," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 283-300, January.
    18. Alexandre M. Florio & Nabil Absi & Dominique Feillet, 2021. "Routing Electric Vehicles on Congested Street Networks," Transportation Science, INFORMS, vol. 55(1), pages 238-256, 1-2.
    19. Yu, Vincent F. & Anh, Pham Tuan & Baldacci, Roberto, 2023. "A robust optimization approach for the vehicle routing problem with cross-docking under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    20. Felipe Araya & Katherine Olivari & Luis A. Salazar & Omar Sánchez & Leonardo Sierra-Varela & Briguitte Neculman, 2024. "Impact of COVID-19 Pandemic on Construction Professionals’ Skills: A Case Study of Chile," Sustainability, MDPI, vol. 16(17), pages 1-23, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2087-:d:1428238. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.