A Smart Decision Support Approach for Sustainable Placement of Waste Bank Using Location-Allocation Models: A Case Study in Gaziantep

Effective waste management has become increasingly important in smart urban design as cities work to become more sustainable and data driven. In this study, we present a smart decision support approach designed to optimize the placement of waste bank points in line with zerowaste project. Within the scope of the paper, fifty-six potential demand and source points in fifteen regions in Gaziantep Şehitkamil district were identified. P-median, P-center, weighted P -median and weighted P -center models were applied to determine the best locations. These models are implemented for two different scenarios where standard and demand density and population are considered. The proposed weighted models are dynamic, and all models applied in the problems were solved using Python Gurobi library and optimal solutions were obtained. The results provide applicable recommendations for urban planners working on sustainable waste management strategies. As a result, this study contributes to the process of building smarter and more sustainable cities.