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Volume 14, Issue 3 (Iranian Journal of Ergonomics-In Press 2026)
Iran J Ergon 2026, 14(3): 0-0 |
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Salmanzadeh H, Mirhaji Moghanjoughi A. Developing a Mixed-Integer Quadratic Programming Model for Equitable Construction Task Allocation to Mitigate Cumulative Low-Back Load Based on the MDD Model. Iran J Ergon 2026; 14 (3)
URL: http://journal.iehfs.ir/article-1-1167-en.html
URL: http://journal.iehfs.ir/article-1-1167-en.html
1- Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran. , h.salmanzadeh@kntu.ac.ir
2- Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran.
2- Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran.
Abstract: (882 Views)
Background and Objectives: Low back musculoskeletal disorders are among the major concerns in the construction industry and are primarily caused by biomechanical loads imposed on the lower back. Previous studies on task allocation have mainly focused on reducing maximum physical risk and, in some cases, psychological risk, while ergonomic indices have predominantly been assessed using qualitative or semi-quantitative methods. However, fairness in the distribution of risk and working time among workers has received less attention. Therefore, this study was conducted to develop a model for reducing risk and ensuring its equitable distribution, as well as the equitable distribution of working time. From a macroergonomic perspective, such a model can enhance personnel motivation and prevent tensions arising from perceived inequality in the workplace.
Methods: This cross-sectional study employed a mathematical modeling approach. Postural and force exertion data were collected from four construction workers performing nine distinct tasks. Compressive forces on the lumbar region were determined using 3DSSPP software. Subsequently, the quantitative risk associated with force intensity and exposure duration was computed using the Mainz-Dortmund Dosis Model (MDD), following which a mathematical model was formulated to facilitate the fair assignment of tasks.
Results: Implementation of the developed mixed-integer quadratic programming model revealed that, under divisible task allocation, the cumulative low-back risk and static exposure time per worker were 5,138 newton-hours(Nh) ( below the permissible threshold of 5,500) and 1.575 hours, respectively. Furthermore, the objective function's proximity to zero substantiates the equitable distribution of both risk and working time.
Conclusion: While maintaining operational constraints, the proposed model improves ergonomic equity and can be used as a decision-making tool to protect workers’ lumbar region
Methods: This cross-sectional study employed a mathematical modeling approach. Postural and force exertion data were collected from four construction workers performing nine distinct tasks. Compressive forces on the lumbar region were determined using 3DSSPP software. Subsequently, the quantitative risk associated with force intensity and exposure duration was computed using the Mainz-Dortmund Dosis Model (MDD), following which a mathematical model was formulated to facilitate the fair assignment of tasks.
Results: Implementation of the developed mixed-integer quadratic programming model revealed that, under divisible task allocation, the cumulative low-back risk and static exposure time per worker were 5,138 newton-hours(Nh) ( below the permissible threshold of 5,500) and 1.575 hours, respectively. Furthermore, the objective function's proximity to zero substantiates the equitable distribution of both risk and working time.
Conclusion: While maintaining operational constraints, the proposed model improves ergonomic equity and can be used as a decision-making tool to protect workers’ lumbar region
Keywords: Musculoskeletal Diseases, Task Allocation, Construction Industry, Ergonomic Equity, Optimization
Type of Study: Research |
Subject:
Musculoskeletal Disorders
Received: 2026/08/14 | Accepted: 2026/10/2 | ePublished: 2026/10/2
Received: 2026/08/14 | Accepted: 2026/10/2 | ePublished: 2026/10/2
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
