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

Eric Forcael (), Ibzan Carriel, Alexander Opazo-Vega, Francisco Moreno (), Francisco Orozco, Rubén Romo () and Duzgun Agdas
Additional contact information
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

Mathematics, 2024, vol. 12, issue 13, 1-23

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.

Keywords: artificial bee colony; swarm intelligence; route optimization; safety distance; hazard analysis; buildings (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/13/2087/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/13/2087/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:13:p:2087-:d:1428238

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().