Kurt, AtilGumus, Mehmet2026-01-242026-01-2420250361-19812169-4052https://doi.org/10.1177/03611981251318338https://hdl.handle.net/20.500.12868/5128This paper discusses the dynamics of supply chain network optimization, specifically focusing on the role of cross-docking. As experienced by the disruptions of the COVID-19 era, external events can trigger supply chain interruptions, necessitating temporary storage solutions. The study examines a network with diverse suppliers, retailers, products, and hybrid cross-docking (HCD) facilities, wherein both transshipment and short-term inventory with restricted storage-age are permitted. Routing of goods from suppliers to retailers encompasses both direct paths and intermediate HCD points, involving multiple truck types. Importantly, all shipments are subject to a carbon tax, factoring in the imperative of mitigating carbon emissions. A dynamic mixed-integer linear programming model is formulated, alongside a greedy-type heuristic algorithm, to optimize the system's total cost. Various computational experiments are used to evaluate the efficacy and solution quality of these methods. Extensive sensitivity analysis, complemented by statistical tests, dissects the impact of various model parameters within the computational experiments. Findings show that allowing storage at HCD facilities, with limited holding time, does not increase system-wide costs but instead bolsters supply chain flexibility. Moreover, carbon tax requires a shift in truck-type selection and plays an important role in reducing the total load-distance traveled, and, therefore, the total carbon emissions.eninfo:eu-repo/semantics/closedAccessfreight planning and logisticstransportation network modelingoptimizationtransportation and sustainabilitytransportation and economic developmentArticle10.1177/03611981251318338267964504702-s2.0-105004004155Q2WOS:001475111700001Q3