A systems engineering framework for the optimization of food supply chains under circular economy considerations

The current linear take-make-waste-extractive model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

The current linear take-make-waste-extractive model leads to resource depletion and environmental degradation. Circular Economy aims to address these impacts through re-utilization of products, renewable energy sources, and closing material loops. This study introduces a novel system engineering framework and decision-making tool for modeling and optimizing food supply chains, using a mixed-integer linear programming model. A case study on the coffee supply chain demonstrates different energy and environmental efficiencies under various product demand scenarios, highlighting the potential benefits of transitioning towards a circular economy.