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

Chethana Chandrasiri, Subodha Dharmapriya, Janappriya Jayawardana, Asela K. Kulatunga (), Amanda N. Weerasinghe, Chethana P. Aluwihare and Dilmini Hettiarachchi
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Chethana Chandrasiri: Department of Manufacturing and Industrial Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya 20400, Sri Lanka
Subodha Dharmapriya: Department of Manufacturing and Industrial Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya 20400, Sri Lanka
Janappriya Jayawardana: Department of Manufacturing and Industrial Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya 20400, Sri Lanka
Asela K. Kulatunga: Department of Manufacturing and Industrial Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya 20400, Sri Lanka
Amanda N. Weerasinghe: National Institute of Post Harvest Management of Sri Lanka, Anuradhapura 50000, Sri Lanka
Chethana P. Aluwihare: National Institute of Post Harvest Management of Sri Lanka, Anuradhapura 50000, Sri Lanka
Dilmini Hettiarachchi: National Institute of Post Harvest Management of Sri Lanka, Anuradhapura 50000, Sri Lanka

Sustainability, 2022, vol. 14, issue 19, 1-20

Abstract: 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.

Keywords: supply chain; banana; configuration; optimization/simulation; GWP; post-harvest losses (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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