A New Integrated Mathematical Model for Agro-Food Supply Chain

Fikry, I.; Gheith, Mohamed; Eltawil, Amr B.

doi:10.1109/iciea52957.2021.9436807

Cited by 1 publication

(1 citation statement)

References 17 publications

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“…Various studies have been performed on finding approaches to make the perishable food supply chain sustainable. Economic sustainability has been studied, focusing on productivity [6][7][8][9][10][11], profit [12][13][14][15][16][17][18][19][20][21][22][23], cost [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40], and revenue optimization [41,42].…”

Section: Introductionmentioning

confidence: 99%

Mitigating Environmental Impact of Perishable Food Supply Chain by a Novel Configuration: Simulating Banana Supply Chain in Sri Lanka

et al. 2022

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As the world is moving into a sustainable era, achieving zero hunger has become one of the top three Sustainable Development Goals, applying a considerable amount of pressure on the agri-food systems to make decisions contemplating the sustainability dimensions. Accordingly, making effective supply chain decisions holistically while achieving sustainability goals has become a major challenge faced by the present agri-food systems. Thus, to address the challenge, a novel supply chain configuration addressing multiple supply chain decisions to reduce global warming potential (GWP) and post-harvest losses have been presented by taking the banana supply chain in Sri Lanka as a case study. In the proposed approach, farmers have been clustered based on their geo positions using K-Means clustering followed by route planning within clusters using a heuristics approach. Retailer points are catered by assigning to wholesalers optimally modeling as an assignment model and then route planning executed using a heuristic approach. The solution generated from the above approaches has been implemented on a simulation platform to calculate the overall supply chain performance including the transportation component, in terms of the net GWP, post-harvest losses, and lead time including routing operations. Simulated supply chain performance has been compared with the existing system and verified the performance of the proposed supply chain configuration. The suggested configuration has reduced the net GWP by 15.3%, post-harvest loss by 2.1%, lead time by 28.2%, and travel distance by 20.47%. The proposed configuration can be further improved by adding dynamic characteristics to the model.

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