Designing a green meat supply chain network: A multi-objective approach

Fatemeh Mohebalizadehgashti, Hossein Zolfagharinia and Saman Hassanzadeh Amin

International Journal of Production Economics, 2020, vol. 219, issue C, 312-327

Abstract: Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this paper, environmental concerns are considered in formulating a mathematical model to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. We develop a multi-objective mixed-integer linear programming formulation to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization of facilities. To demonstrate the efficiency of the proposed optimization model, we design a green meat supply chain network for Southern Ontario, Canada. A solution approach based on augmented ε-constraint method is employed to solve the proposed model. As a result, a set of Pareto-optimal solutions is obtained. The set of Pareto-optimal solutions gives decision-makers the opportunity to make a trade-off between economic, environmental, and capacity utilization objectives. Our example shows that it is possible to keep emissions reasonably low without incurring high total costs. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature.

Keywords: Meat supply chain; Decision tree; Multi-objective programming; Mixed-integer linear programming; Augmented ε-constraint (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:219:y:2020:i:c:p:312-327

DOI: 10.1016/j.ijpe.2019.07.007

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