Abstract
Within the construction project management, environmental concerns often outweigh time and cost considerations. However, with increasing awareness of the air pollution stemming from construction activities, there arises a critical necessity to balance time, cost, and environmental impact (measured in Equivalent-KgCO2). Traditional algorithms have struggled to effectively handle the multitude of non-dominated solutions, leading to a scarcity of better-quality Pareto-optimal solutions. To overcome this challenge, this paper recommends a novel methodology employing the Non-dominated Sorting Genetic Algorithm III (NSGA-III) to construct a model for optimizing the trade-off between time, cost, and environmental impact in construction projects. Latin Hypercube Sampling (LHS) is incorporated into NSGA III for population initialization, resulting in the development of LNSGA III. The developed LNSGA III model aims to efficiently navigate the intricate trade-offs inherent in construction projects. The efficiency of the proposed method is demonstrated by solving a case study project, which generates an exhaustive set of Pareto-optimal solutions. A comparison with existing algorithms demonstrates the superiority of LNSGA III. These solutions provide decision-makers with the flexibility to select the most suitable and sustainable options for activities execution based on their expertise and project-specific considerations.
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Puja Bohra conducted the data analysis and wrote the manuscript. Ram Swaroop Verma reviewed and finalized the manuscript.
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Bohra, P., Verma, R.S. Optimizing sustainable construction projects through LNSGA III: a time-cost-environmental impact trade-off approach. Asian J Civ Eng (2024). https://doi.org/10.1007/s42107-024-01052-6
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DOI: https://doi.org/10.1007/s42107-024-01052-6