Multiobjective Optimization for Improving Sustainable Equipment Options in Road Construction Projects
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 1
Abstract
The increasing awareness of sustainability has resulted in the progressive regulation of contractors for public projects to lower the pollution associated with their equipment fleet. Nevertheless, such implementation has not been fully developed yet due to the challenges this presents to contractor profitability and the practical usefulness of decision-support tools. This paper developed a sustainable equipment fleet (SEF) decision-support optimization model with the capability to reduce the emissions of construction equipment and to minimize the equipment fleet modification cost, subject to the contractor’s budget and time constraints. The model utilizes a multiobjective genetic algorithm (GA) to search for the combination of equipment utilization, equipment model, and sustainable options that provide the optimal equipment fleet options to contractors. The results from the case study of a road construction project demonstrated the tradeoff between emissions and costs, with a wide range of optimal sustainable equipment fleet options. In addition, the fuel equivalent ratio (FER) and the equipment cost-effective ratio (CER) were newly established to normalize pollutant generation and equipment investment and to enable equipment comparisons for facilitating equipment selection by the contractor. The findings suggested that equipment selection involving a lower FER is preferable for sustainability and likewise, a lower CER for the cost aspect. However, effectiveness was measured as the proportion of FER to CER, with higher effectiveness when the proportion was lower. This paper facilitates the assessment and prioritization by construction companies of their equipment investment options to satisfy sustainability requirements.
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Data Availability Statement
The data generated and analyzed during the study are available from the corresponding author on request.
Acknowledgments
This research is supported in part by the Graduate Program Scholarship from the Graduate School, Kasetsart University, Bangkok, Thailand. However, any opinions, findings, and recommendations in this paper are those of the authors and do not necessarily reflect any opinions of the funding agency.
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Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 1 • January 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 7, 2022
Accepted: Sep 6, 2022
Published online: Nov 12, 2022
Published in print: Jan 1, 2023
Discussion open until: Apr 12, 2023
ASCE Technical Topics:
- Business management
- Construction engineering
- Construction equipment
- Construction industry
- Construction management
- Contracts and subcontracts
- Engineering fundamentals
- Equipment and machinery
- Highway and road management
- Highway transportation
- Highways and roads
- Infrastructure
- Infrastructure construction
- Models (by type)
- Optimization models
- Practice and Profession
- Project management
- Sustainable development
- Transportation engineering
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