Automation in Construction, Volume (160), Year (2024-4) , Pages (105317-105336)

Title : ( Bi-level integration of discrete-event simulation (DES) and social force modeling (SFM) for construction labor productivity )

Authors: mahdi naeimirad , Mojtaba Maghrebi ,

Citation: BibTeX | EndNote

Abstract

Optimizing construction labor productivity is a challenge due to the inherent uncertainties of construction projects. While increasing the workforce size is often perceived as a strategy to enhance productivity, it can lead to increased physical interactions and workspace interference. This paper presents a framework for assessing the construction productivity, taking into account spatial constraints, labor interactions, and the dynamic nature of the workspace. The proposed model effectively captures the influence of workforce dynamics on construction activity productivity by integrating two techniques: Discrete-Event Simulation (DES) and Social Force Modeling (SFM). DES replicates the workflow, while SFM simulates worker interactions and movements. A real-world case study validates the model\\\\\\\'s ability to simulate construction scenarios realistically. The model can effectively capture how productivity varies depending on the number of workers, workspace layout, and project progress. The model can empower engineers with valuable insights into labor productivity optimization, leading to more efficient construction projects.

Keywords

, ProductivitySocial force modelingDiscrete, event simulationWorkspace
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@article{paperid:1097720,
author = {Naeimirad, Mahdi and Maghrebi, Mojtaba},
title = {Bi-level integration of discrete-event simulation (DES) and social force modeling (SFM) for construction labor productivity},
journal = {Automation in Construction},
year = {2024},
volume = {160},
month = {April},
issn = {0926-5805},
pages = {105317--105336},
numpages = {19},
keywords = {ProductivitySocial force modelingDiscrete-event simulationWorkspace},
}

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%0 Journal Article
%T Bi-level integration of discrete-event simulation (DES) and social force modeling (SFM) for construction labor productivity
%A Naeimirad, Mahdi
%A Maghrebi, Mojtaba
%J Automation in Construction
%@ 0926-5805
%D 2024

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