Algorithmic solutions for warehouse site selection using complex pythagorean fuzzy soft sets in supply chain management

Abstract

Abstract Global trade heavily depends on effective supply chain management and the strategic placement of distributors. Additionally, customer demands are becoming increasingly diverse and dynamic, with each customer expecting prompt and reliable responses from companies or distribution centers. To ensure a fast and efficient delivery process, businesses are striving to make well-informed decisions about the site selection of distribution centers or warehouses. The growth and success of online businesses, such as those on Amazon, largely hinge on the strategic site selection of their warehouses to expedite supply chain operations. This site selection process requires a comprehensive analysis of various factors. However, collecting and processing the relevant data often involves uncertainties and fuzziness. To address these challenges, the proposed research introduces a novel algorithmic approach based on distance measures within the Complex Pythagorean Fuzzy Soft Set (CPFSS) framework. The research presents the formulation of distance measures for the CPFSS, followed by the development of an algorithm. This algorithm is then applied to a real-life case study for the site selection of a warehouse for a company named HCRFT, which specializes in handicrafts. Furthermore, a detailed comparison between the proposed approach and existing models is conducted to validate and demonstrate the effectiveness of the algorithm. Finally, concluding remarks summarize the findings and implications of the study.