Optimizing sustainable hub depot locations for empty container logistics in Slovenia using particle swarm optimizationTuljak Suban, Danijela (Avtor) particle swarm optimizationempty container repositioninghub depotoptimizationminimizing CO2 emissionsenergy science and technologymathematics and computingContainers account for 16% of all tonnage transported by sea. Therefore, the efficient repositioning of empty containers is a necessary, albeit often unprofitable, activity. This process supports both the local and global efficiency of container transport, especially given the significant imbalance in container flows from Asia to Europe. The transport sector is responsible for 21.2% of total CO2 emissions, making Empty Container Repositioning (ECR) crucial from an environmental perspective. Efficient repositioning and the identification of an optimal location for an empty container depot are crucial problems that can be effectively solved within a hub system. The aim is to find solutions that minimize the overall impact on the environment while reducing holding and travel costs. This paper proposes a robust and feasible method for determining the optimal location for an inland empty container depot, demonstrating its effectiveness on a large-scale logistics hub location problem in Slovenia. The proposed method takes into account both the economic costs and the emissions generated during the repositioning process and aims to select a hub location that minimizes these factors. The optimization is performed using a heuristic approach, Particle Swarm Optimization (PSO), which requires fewer constraints and assumptions compared to traditional linear optimization techniques. This method takes advantage of the behavior of swarms and their ability to find optimal solutions to complex problems. In contrast to classical approaches such as linear programming, which require considerable effort to formulate and solve, this method simplifies the process and efficiently identifies optimal solutions.20252025-12-22 08:54:46Članek v reviji177363sl