Using the clustering method to find the final environmental parameters coefficients in road construction projects - Eshagh Rasouli Sarabi; Ramin Vafaei Poursorkhabi; Mehdi Ravanshadnia (Scientific Reports, 2025)
Abstract Nowadays, more and more attention is being paid to environmental issues due to the development of road transportation, particularly the construction of arterial roads. Despite the existence of diverse methods to determine convenient criteria for their assessment, determining the projects with the least harmful effects on the environment and ranking them for purposes of budget allocation and prioritization are remarkably important. The case is more highlighted in regions where roads go through diverse areas with different climatic and geographical distributions. In the present study, a new method consisting of two phases was proposed to determine the optimal coefficient of environmental parameters in road construction parameters. In the first phase, the Genetic Optimization Algorithm was implemented to determine convenient coefficients for the relevant parameters. During this stage, similar coefficients were clustered together. In the second phase, an environmental index for various projects was determined based on the obtained results, and the proposed projects were ranked based on that. According to the results obtained concerning environmental parameters during the pre-implementation stage, polluting water resources was the most influential parameter, with a coefficient determined at 3.59. Moreover, the most significant parameter during the implementation was noise pollution, with a coefficient of 5.89, while damaging the ecosystem was the most significant one during the stage of land use change (5.25). Furthermore, soil pollution was the most remarkable parameter during the stage of maintenance (5.81), while damaging the local climate pollution was the most important one during the stage of road implementation (5.67). The above findings can be helpful for researchers in road construction projects.