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Adaptive LOB scheduling for optimizing resource leveling and consumption

    Ayman Altuwaim Affiliation
    ; Eid Alagha Affiliation
    ; Abdulrahman Bin Mahmoud Affiliation
    ; Dina A. Saad Affiliation

Abstract

Several techniques were developed to improve resource allocation in construction projects, yet few in repetitive construction projects. Accordingly, this research aims at minimizing resource consumption and fluctuations using Line-of-Balance (LOB) repetitive scheduling technique. An optimization model has been developed consisting of three modules: LOB schedule module, resource leveling module, and optimization module. The model helps determine the optimum (a) start time for each activity considering any needed delays to level resources, (b) number of crews travelling from one unit to another, (c) unit to change the number of crews, and (d) the new changed number of crews. Unlike the existing efforts, the developed model provides the capabilities of (a) allowing the change of number of crews of an activity at a certain repetitive unit to increase or decrease the progress rate; and (b) accommodates non-serial repetitive projects to enhance the model’s practicality. Using a pipeline project, the model outperformed the existing LOB-based models in minimizing resource consumption and fluctuations within the desired project duration. This study offers the project planners a useful tool to efficiently utilize their projects’ resources and avoid hidden costs due to inefficient resource utilization on-site as well as overcoming shortage in resource availability.

Keyword : repetitive scheduling, resource-constrained scheduling, resource leveling, optimization, resource allocation, line of balance

How to Cite
Altuwaim, A., Alagha, E., Mahmoud, A. B., & Saad, D. A. (2024). Adaptive LOB scheduling for optimizing resource leveling and consumption. Journal of Civil Engineering and Management, 30(3), 220–233. https://doi.org/10.3846/jcem.2024.20952
Published in Issue
Mar 12, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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