<p>This study investigates the location-routing problem in the pallet pooling system, which is an extended combinatorial optimization problem in the field of logistics management. A mixed-integer linear programming model is formulated for the location-routing problem, incorporating simultaneous pickup and delivery, and the limitations on carbon emissions and transportation time. To address the demand uncertainty, this study extends the model using a robust optimization approach to enhance solution reliability. Due to the NP-hard nature and high computational complexity of the problem, a heuristic algorithm integrating genetic algorithm and ant colony optimization is developed to obtain efficient solutions. Numerical experiments are conducted on classical benchmark instances to validate the model feasibility, demonstrate that the integrated optimization model outperforms the two-stage model, and highlight the superior performance of the heuristic algorithm in terms of solution quality and computational efficiency. Furthermore, the study provides valuable insights for logistics managers in the pallet pooling system.</p>