Optimizing an Innovative Warehousing Solution

This thesis is part of the development of an innovative robotic industrial storage system designed by the startup Altikap. The system consists of single- or double-depth angle-bracket shelving that allows for fine-tuning of storage heights, shelves of varying dimensions, an autonomous mobile module that transports goods, and fixed workstations (for picking or loading). The resulting architecture makes it possible to significantly increase storage density (by 2 to 4 times the volume occupied) while improving the ergonomics and productivity of operations. The central focus of this thesis is the planning and control of the mobile module’s operations: the goal is to determine, either in advance or in real time, the optimal sequence of movements for retrieving shelves from the warehouse, transporting them to workstations, and then efficiently returning them to storage after processing. This combinatorial problem is unprecedented in the literature: it combines constraints related to sequencing, three-dimensional storage, and vertical obstruction, with no direct equivalent among problems in the literature. The approach taken centers on the formal mathematical modeling of the problem, the development of exact and approximate solution methods, and their validation using real-world industrial data. The results will be integrated into the warehouse management system developed by Altikap and featured in international scientific publications.