An outranking approach for selecting the best warehouse location in Konya using spherical fuzzy rough numbers

In order to store and oversee inventory, raw materials, or finished goods in different Konya regions, warehouse building management is a challenging task for the authorities that calls for creative and efficient distribution operations. Choosing the ideal site for warehouse facility is typically a difficult procedure, particularly when taking into account a number of parameters.Due to the costs of purchasing the property and associated improvements, the location selection problem is a long-term investment decision; as such, it should be carefully considered using a reliable method to avoid the negative consequences that follow bad decisions. To handle the inherent complexity and numerous ambiguities in real-world circumstances, the problems underlying warehouse management require the application of appropriate multi-criteria decision-making techniques. The goal of the present study is to develop an integrated spherical fuzzy rough number based -Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method. Through the spherical fuzzy rough ideal and anti-ideal solutions, the spherical fuzzy rough-MARCOS technique yields the reference points and allows for a more accurate assessment of alternatives via utility degree. The study’s emphasis on appropriately evaluating the criterion weights utilizing the spherical fuzzy rough -Stepwise Weight Assessment Ratio Analysis (SWARA) algorithm to ascertain the viability of the decisions and reduce the decision-makers’ personal impact. To address ambiguity and imprecision in expert assessment, the spherical fuzzy rough numbers are employed throughout the examination process. To demonstrate how the recommended decision-making methodology may be applied to select the ideal location for warehouses, a case study of Konya is resolved. Our proposed method is compared with two current multi-criteria decision-making techniques, namely the spherical fuzzy rough-TOPSIS method and spherical fuzzy rough-WASPAS, in order to confirm the consistency of results. Sensitivity analysis is applied to verify if the recommended method’s computations are appropriate.