With the rise of e-commerce and the acceleration of global trade, effective cargo-packing strategies have become increasingly important to reduce logistics costs and improve transportation efficiency. This study proposes a new boxing optimization algorithm (BoxPA), which is specifically designed to optimize the boxing strategy for land transportation logistics under the business-to-business (B2B) model. By combining traditional space utilization theory with modern computing technology, we developed a system that can automatically generate optimal boxing configurations. The input of the algorithm includes container size, box collection, and stacking strategy, and it continuously improves the packing configuration through an iterative process and finally outputs a packing plan that maximizes efficiency. Experimental results show that BoxPA provides a feasible solution for cargo loading problems within five seconds for a regular cargo container. In the four real-world scenarios, the proposed BoxPA can calculate one optimal solution that the container space is utilized perfectly. In other words, the proposed BoxPA is feasible for real-world implementation.