Prediction and improvement of labor productivity using hybrid system dynamics and agent-based modeling approach

Abstract

Purpose The purpose of this paper is to present a hybrid simulation approach for predicting the value of labor productivity taking account of various continuous influencing factors and the interactions between different agents involved in the project. Design/methodology/approach The various continuous factors affecting labor productivity are simulated using system dynamics (SD). The heterogeneity of different agents involved in the project and their interactions is accounted using agent-based modelling (ABM). The developed ABM and SD models are finally integrated to simulate the value of labor productivity taking account of all the influencing factors. Findings The proposed hybrid simulation tool is implemented in a real project to evaluate its perfomance. The value of labor productivity is simulated by taking account of all the influencing factors. The most appropriate execution strategy is then selected using the developed hybrid SD-ABM approach to improve productivity. It is shown that the number of working groups and their movement patterns affect the severity of the groups’ interferences which will in turn affect the value of labor productivity. Practical implications This research helps project managers to predict and improve the value of labor productivity taking account of all the influencing factors. Originality/value It is believed that the proposed hybrid SD-ABM simulation approach offers a novel and robust tool for modeling labor productivity because the effects of various continuous influencing factors and the interactions between different agents are taken into account through the combination of SD and ABM. Many complex problems faced in construction projects involve interacting elements of a different nature, and the integration of SD with ideas from ABM offers potential to combine the strengths of the two methodologies to solve the problem.

Overview of construction simulation approaches to model construction processes

“…There was a constant flow of information between the models (Nasirzadeh et al, 2018). Khanzadi et al (2017) also used an integrated SD-ABM simulation approach to see how site congestion affects productivity.…”

“…Since then, several different approaches have been proposed. The existing literature on construction simulation mostly uses one of the following as case studies: earthworks -e.g., AbouRizk and Halpin (1992), Lorterapong and Moselhi (1996), and Alzraiee et al (2012); reinforced concrete works -e.g., Moradi et al (2015), Khanzadi et al (2017), and Nojedehi and Nasirzadeh (2017); or civil engineering works -e.g., AbouRizk and Sawhney (1993), Robinson Fayek and Oduba (2005), and AbouRizk (2010), which are mostly machinedriven works. However, it is arguably more important to simulate labor-driven operations because labor resources (especially skilled) tend to be scarcer and contain more risk than do equipment or materials.…”

Input for Hybrid Simulation Modelling Construction Operations

“…Khanzadi et al [41] suggested an SD-ABM hybrid simulation approach to improve productivity. The SD component contained the influencing factors, while the ABM part had groups of workers as agents and was used to model site congestion.…”

A framework for modelling masonry construction using hybrid simulation approaches

“…There was constant information flow between the models [34]. Khanzadi et al [6] also used an integrated SD-ABM simulation approach to see how site congestion affects productivity.…”

“…Most of the existing literature on construction simulation introduces earthworks (see, for example, AbouRizk and Halpin [3], Alzraiee, Zayed and Moselhi [4], Lorterapong and Moselhi [5]), reinforced concrete works (see, for example, Khanzadi et al [6], Moradi, Nasirzadeh and Golkhoo [7], Nojedehi and Nasirzadeh [8]) or civil engineering works (see, for example, AbouRizk and Sawhney [9], AbouRizk [10], Robinson Fayek and Oduba [11]) as case studies, which are mostly machine-driven works. However, it is arguably more important to simulate labour-driven works as labour resources tend to be scarcer (especially skilled) and more risks are involved with them than with equipment or materials.…”