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Today's automotive factories are essentially assembly plants that receive parts from a vast network of suppliers around the world. Transporting thousands of part types over very long distances is a major logistic problem whose solution is a critical factor in the factory management. In this study we have developed a statistical and optimization methodology implemented in a software tool to help the decision makers select the most appropriate container for each part. A key element is to determine the number of parts that fit in a given container. Two optimization procedures have been developed, depending on the type of part, and used to calculate costs of each container. These costs include not only transporting parts from supplier to factory, but also the costs of handling parts within the factory and returning the empty containers to the supplier. • Selection of optimal container for parts transport from suppliers to assembly plant. • A new method estimates the number of parts in a container when loaded in bulk. • An algorithm optimizes parts in a container via strategic placement, not bulk loading. • Software integrates databases, geometry, optimization, learning and economic analysis. • The software, validated in the real world, is used by a major vehicle manufacturer. [ABSTRACT FROM AUTHOR]