Abstract
Supply chain and global logistics are driven by strategically focusing on core competences, outsourcing manufacturing to pursue higher value proposition in the supply chain, radically improving the return of capital investments and providing total solutions to targeted customers. The container-loading research has important industrial and commercial application for global logistics. In practice, loading pooled shipment into containers is a complex procedure that has relied largely on the workers’ experience. We developed an efficient computational procedure involving three-dimensional cutting for determining near-optimal container-loading patterns to minimize the waste of container space. We used numerical examples from a motor company that imports key components from Japan, produces parts in Taiwan, and assembles cars in China to estimate its validity and discussed the effectiveness of the proposed solution. This study concludes with a discussion of future research.