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| Title: | Perishable supply chain model for sustainable and customer-oriented logistics management using model predictive control | | | Authors: | T. Hipolito, D. Gomes, J. Lemos Nabais, M. Ayala Botto, R.R. Negenborn |
| | Conference: | 5th LAETA Young Researchers Meeting (LAETA 2022) | | Address: | Lisbon, Portugal | | Date: | May 2022 |
| | Abstract: | Customer service level and sustainability are currently two of the main drivers of supply chain decision makers. Commonly, supply chains are designed and operate to maximize the profit, to maximize customer service level or to minimize the operational cost. However, designing supply chains considering sustainable features as the main goal, such as eliminating goods wastage and reducing greenhouse gas emissions, while still achieving high customer service levels might create a competitive advantage. Building on previous model predictive control approaches, this paper proposes an integrated and modular perishable supply chain model, defined by a set of parameters, that describes the dynamics of material flows. The proposed model describes the handling of perishable goods from upstream to downstream considering simultaneously multiple echelons, multiple players per echelon and multiple commodities with distinct lifetimes. Besides, it monitors the time until expiration of perishable goods and identifies when they get spoiled. The proposed model feeds a Model Predictive Control framework that performs the logistics management of perishable supply chains considering maximum service level. Furthermore, performance metrics are designed to quantify and evaluate the performance of the Model Predictive Control framework and numerical experiments considering two network configurations are performed. Then, a quantitative analysis of the supply chain performance is shown and a qualitative analysis focusing on the handling of the goods, namely, production, storage and transportation. Lastly, managerial insights are discussed and possible future work is highlighted. |
| | Reference: | Perishable supply chain model for sustainable and customer-oriented logistics management using model predictive control. T. Hipolito, D. Gomes, J. Lemos Nabais, M. Ayala Botto, R.R. Negenborn. In Proceedings of the 5th LAETA Young Researchers Meeting (LAETA 2022), Lisbon, Portugal, May 2022. | | | Request: | A
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