Multiscale production routing in multicommodity supply chains with complex production facilities |
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Affiliation: | 1. Department of Management Science, Lancaster University, Lancaster LA1 4YW, United Kingdom;2. DMEIO, Facultad de Ciencias, Universidad de La Laguna, 38271 Tenerife, Spain;1. IBISC, Univ Evry, Université Paris-Saclay, 91025 Evry, France;2. School of Economics and Management, Fuzhou University, Fuzhou 350116, China;3. School of Economics and Management, Tongji University, 1239 Siping Road, Shanghai 200092, China;4. ESIEE Paris, Université Paris-Est, 2 boulevard Blaise Pascal-BP 99, Noisy-le-Grand Cedex 93162, France;5. College of Economics and Management, Nanjing Agricultural University, Nanjing, China |
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Abstract: | 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. |
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Keywords: | Production routing Supply chain management Production scheduling Multiscale optimization MILP-based heuristic |
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