Black-Hole Heuristics-Based Clustering for Milk-Run Optimization

The optimization of in-plant supply processes can significantly increase the efficiency of production processes. In flexible manufacturing systems and U-shaped cells-based production systems the milk-run supply plays an important role, therefore their optimization is essential. The design of milk-run based materials supply includes a wide range of design aspects including routing, clustering, scheduling and facility location. Within the frame of this article, the author proposes a novel black-hole heuristics-based approach focusing on the clustering problems of milk-run optimization. The new methodology makes it possible to build optimal clusters of supply tasks to support the solution of routing problems. The model focuses on the clustering problems related to the real-time re-clustering and re-routing of scheduled milk-run operations and takes time- and capacity-related constraints into consideration. The described model and the optimization methodology based on black-hole heuristics is validated by case studies. The numerical analysis shows, that the proposed clustering algorithm can improve the efficiency of milk-run routing and can lead to significant cost reduction and virtual emission reduction.