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Robust fresh front distribution centre location problem considering resilience under demand uncertainty.

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Title: Robust fresh front distribution centre location problem considering resilience under demand uncertainty.
Authors: Wang, Qiuhan, Pu, Xujin, Du, Bo, Wei, Jinpeng
Source: International Journal of Production Research; Sep2025, Vol. 63 Issue 17, p6384-6410, 27p
Subject Terms: LOCATION problems (Programming), ROBUST optimization, PERISHABLE goods, DISASTER resilience, WAREHOUSES, MIXED integer linear programming, COST control, UNCERTAINTY (Information theory)
Geographic Terms: WUXI (Jiangsu Sheng, China), CHINA
Abstract: The sales model of front distribution centre (FDC) is gaining prominence in the fresh produce sector. However, the nature of such localised service requires substantial costs. Traditional location models, driven by minimal cost, are prone to neglect the potential interruption risks brought by demand uncertainty. In this study, we propose a novel hybrid expansion strategy, extending the coverage range of candidate FDC, to reduce the fulfilment costs of FDC and mitigate interruption risks. We aim to proactively embed resilience under the location model. Additionally, a bi-objective mixed-integer programming (MIP) model is developed to simultaneously minimise the total cost of FDCs operations while ensuring maximum resilience. To handle uncertainty, the proposed MIP model is transformed into three robust optimisation (RO) models. To validate the proposed approach, comprehensive numerical experiments are conducted based on a real-life case study of Freshippo in Wuxi, China. The results demonstrate that the hybrid strategy of expanding FDC with different service range achieves a better balance between cost and resilience compared to the traditional strategy of limiting the service range of FDC within 3km. The RO models efficiently address uncertainty while maintaining robustness and the R-ellipsoid model reaches the best results among the three RO models. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:The sales model of front distribution centre (FDC) is gaining prominence in the fresh produce sector. However, the nature of such localised service requires substantial costs. Traditional location models, driven by minimal cost, are prone to neglect the potential interruption risks brought by demand uncertainty. In this study, we propose a novel hybrid expansion strategy, extending the coverage range of candidate FDC, to reduce the fulfilment costs of FDC and mitigate interruption risks. We aim to proactively embed resilience under the location model. Additionally, a bi-objective mixed-integer programming (MIP) model is developed to simultaneously minimise the total cost of FDCs operations while ensuring maximum resilience. To handle uncertainty, the proposed MIP model is transformed into three robust optimisation (RO) models. To validate the proposed approach, comprehensive numerical experiments are conducted based on a real-life case study of Freshippo in Wuxi, China. The results demonstrate that the hybrid strategy of expanding FDC with different service range achieves a better balance between cost and resilience compared to the traditional strategy of limiting the service range of FDC within 3km. The RO models efficiently address uncertainty while maintaining robustness and the R-ellipsoid model reaches the best results among the three RO models. [ABSTRACT FROM AUTHOR]
ISSN:00207543
DOI:10.1080/00207543.2025.2472296