Quantified neutrosophic set-based SWARA-VIKOR methodology: An approach to reduce indeterminacy in sustainable urban development

Informed and accurate decision analysis with a minimum level of indeterminacy is very crucial in every multi-criteria decision-making problem. In the proposed research, the MCDM problem of sustainable urban planning and zoning is taken into account. Balanced economic advancement, social welfare, and a sustainable environment are the basic needs of urban planning, but these requirements are occupied with uncertain and ambiguous data. In this paper, a quantified neutrosophic set-based SWARA-VIKOR methodology is proposed to integrate sustainable zoning planning of land use. This proposed methodology is basically a combination of Stepwise Weight Assessment Ratio Analysis (SWARA) and visekriterijumsko kompromisno rangiranje (VIKOR). Its base is the quantified neutrosophic set, which provides a sound algorithm to reduce the indeterminacy factor inherent in the neutrosophic form data of the concerned problem, leading to more accurate and robust results. Furthermore, the graphical visualization of the indeterminacy component specifically is added to clearly represents a reduced and controlled environment for indeterminacy. The relative importance of major criteria is determined by SWARA, and the ranking of land use scenes is established using VIKOR. Furthermore, this methodology is covered with an additional merged step of optimization technique that enhances the reliability and optimizes the solutions. In this rapidly growing urban area environment, a pseudo realistic dataset on various land use circumstances is created and then quantified using a quantified neutrosophic set that effectively minimizes the indeterminacy. The results of the final ranking demonstrate that the proposed approach is more accurate than conventional approaches, as it significantly reduces indeterminacy in the data. This development in decision analysis assists the policymakers and urban planners in a way that they have correct and clear decision analysis systems.