Routing Heuristics for in-House Transportation in Assembly Systems

This research addresses routing challenges in high-variety mass customization environments, focusing on in-house transportation problems involving traversal between supermarket cells and consecutive assembly stations. Supermarket cells are organized separately from assembly stations in parallel rows, each cell having a designated pickup point and each assembly station a drop-off point. The routing problem aims to establish an efficient path, starting from the depot and visiting all pickup and drop-off points exactly once before returning. This study introduces a range of heuristic methodologies tailored to address the problem. These heuristics, such as nearest neighbor, S-shape, modified S-shape, and combined heuristics, are characterized by practical implementability, offering practitioners defined guided rules to navigate the shop floor. Artificial problem instances of varying sizes, characterized by the number of cells and pickup/drop-off points, are analyzed, comparing heuristic performance against an optimal benchmark solution. Results indicate that heuristics perform better in larger problem sizes, particularly with 100 rows, showing average gaps below 11.48% and 1.02% for 7-row and 100-row instances, respectively.