A circular food supply chain network model to reduce food waste

Ozgur Kabadurmus (), Yiğit Kazançoğlu, Damla Yüksel and Melisa Özbiltekin Pala
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Ozgur Kabadurmus: Clemson University
Yiğit Kazançoğlu: Yasar University
Damla Yüksel: Yasar University
Melisa Özbiltekin Pala: Yasar University

Annals of Operations Research, 2025, vol. 354, issue 2, No 5, 663-693

Abstract: Abstract Food loss and waste (FLW) is a growing global problem throughout the world. The rapid increase in food waste and deficiencies in treatment processes have led to greater harm to the environment. A circular food supply chain (FSC) is now an essential means of encouraging circular economy. Proper food waste treatment and recycling operations can not only benefit the environment, but these wastes can also be used as raw material for production in a circular economy. In this study, a circular food supply chain network model is designed to reduce the food waste generated in the circular food supply chain systems of municipalities. Then, a mixed-integer linear programming model is generated to model the proposed circular food supply chain network model. The MILP model is a network model aimed at reducing the food waste generated. To do so, two objectives are considered: the overall cost of the network is minimized and the amount of distributed food waste from the generation nodes to the end nodes is maximized. Due to the bi-objective nature of the proposed mathematical model, the Improved Augmented Epsilon Constraint method (AUGMECON2) is implemented to solve the problem optimally. To illustrate the applicability and effectiveness of the proposed mathematical model, two real-life case studies were carried out in Izmir, the third largest city in Turkey. The computational results demonstrate that the proposed model is beneficial for both small and large municipalities since it provides the Pareto-optimal set where the total amount of distributed food waste is maximized and the total cost is minimized.

Keywords: Food supply chain; Food waste; Circular economy; Network model; Mixed-integer linear programming; Bi-objective optimization (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10479-022-04728-x

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