With the rising demand for customized products, flexibility in mixed-model assembly lines has become more critical. As product variety increases, so does the number of parts needed at the border of line. However, the space at the border of line is limited. To use this space effectively, appropriate line-feeding policies must be implemented, often requiring parts to be repackaged or kitted in preparation areas—also referred to assupermarkets—before transportation to the border of line. This process results in additional intralogistics costs for preparation and transportation. The goal of this PhD project is to develop a robust framework for tactical planning in line feeding for flexible assembly lines. This research focuses on minimizing material handling costs, including repackaging, kitting, transportation to the supermarket and the border of line, and the assembly operators’ walking and picking activities. Additionally, the research involves creating optimization algorithms to generate tactical plans based on demand forecasts, accounting for uncertainties in product mix and volumes. By advancing current models, this research seeks to support a wider range of intralogistics options and improve flexibility and efficiency in assembly line feeding and intralogistics design.