In this work, we introduce the multiscale production routing problem (MPRP), which considers the coordination of production, inventory, distribution, and routing decisions in multicommodity supply chains with complex continuous production facilities. We propose an MILP model involving two different time grids. While a detailed mode-based production scheduling model captures all critical operational constraints on the fine time grid, vehicle routing is considered in each time period of the coarse time grid. In order to solve large instances of the MPRP, we propose an iterative MILP-based heuristic approach that solves the MILP model with a restricted set of candidate routes at each iteration and dynamically updates the set of candidate routes for the next iteration. The results of an extensive computational study show that the proposed algorithm finds high-quality solutions in reasonable computation times, and in large instances, it significantly outperforms a standard two-phase heuristic approach and a solution strategy involving a one-time heuristic pre-generation of candidate routes. Similar results are achieved in an industrial case study, which considers a real-world industrial gas supply chain.
Bibliographical noteFunding Information:
The financial support from the National Science Foundation under Grant no. 1159443 and from Praxair is gratefully acknowledged. Furthermore, the authors would like to thank Prof. Carlos A. Méndez from the National University of Litoral for early discussions on potential solution approaches.
- MILP-based heuristic
- Multiscale optimization
- Production routing
- Production scheduling
- Supply chain management