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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
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    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)

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