Towards Sustainable Urban Futures: Integrating a Novel Grey Multi-Criteria Decision Making Model for Optimal Pedestrian Walkway Site Selection

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Abstract

Today, urban development faces complex global challenges that require new approaches to influence its practices and policies. By prioritizing sustainability, mobility, and community resilience, we are moving towards a holistic approach that protects the well-being of residents and the environment. In this dynamic urban design environment, finding ways to identify pedestrian-friendly spaces and create safe, efficient, and sustainable urban environments is a major challenge, and it requires research that seeks to optimize this choice, especially in terms of integrating numerical modeling methods and a wide range of measurement tasks. This research is concerned with optimizing pedestrian accessibility, which directly contributes to reducing environmental impact, improving non-motorized transport, and reducing traffic congestion. It integrates a novel, mixed multi-criteria decision-making (MCDM) model that benefits from the use of Grey’s theory. This research’s purpose goes beyond addressing cities’ immediate challenges; it seeks to contribute to a broader understanding of sustainable urban planning. This study represents a pioneering effort to identify the challenges of optimal site selection for pedestrian walkways. By using a multi-criteria decision-making approach based on mathematical modelling and facility engineering, this effort addresses gaps in the current understanding of site selection criteria and aims to lead a paradigm shift toward a sustainable, efficient, and inclusive urban environment. The results show that the updated RANCOM-PIV greyscale is quite robust and reliable, when comparing the final results of the PIV greyscale and the MARCOS greyscale.

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APA

Reyes-Norambuena, P., Martinez-Torres, J., Nemati, A., Hashemkhani Zolfani, S., & Antucheviciene, J. (2024). Towards Sustainable Urban Futures: Integrating a Novel Grey Multi-Criteria Decision Making Model for Optimal Pedestrian Walkway Site Selection. Sustainability (Switzerland) , 16(11). https://doi.org/10.3390/su16114437

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