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July 10, 20260 citationsOpen Access

R3PACK WP3 D3.5 Sensitivity Analysis and Multi-Scenario Network Optimization with Guidelines about Risk Hotspots

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RARiccardo AccorsiGBGiorgia BartolottiBGBeatrice Guidani

Key Points

  • The aim is to develop a decision-support model for optimizing reuse logistics networks while addressing carbon emissions.
  • Extended the decision-support model from Deliverable 3.4 to include a carbon emission function.
  • Applied the model to a nationwide scale under various scenarios to analyze consumer behaviors and return rates.
  • Quantified economic impacts associated with CO₂ emission reduction targets and estimated transportation costs.
  • Evaluated the economic effort needed for specific CO₂-equivalent emission reductions across scenarios.
  • Identified logistical implications, such as varying transportation costs and distances under different configurations.

Abstract

This deliverable results from the development and application of the decision-support model for reuse logistics network design presented in Deliverable 3.4, which is hereby extended to include a carbon emission function. This supports the strategic design and planning of the reuse logistics system by explicitly addressing the cost–emission trade-off. The analysis is extended to a nationwide scale to assess the system-level impacts of adopting reusable packaging solutions. The model is implemented using the selected reusable packaging option for each food product and is applied under multiple scenarios to evaluate the influence of consumers’ return and scrap rates associated with reverse logistics operations. For each scenario, the model quantifies the economic effort required to achieve specific CO₂-equivalent emission reduction targets. Additionally, transportation costs and average transport distances are estimated, providing insight into the logistical implications of alternative system configurations.

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Cite This Study

Accorsi et al. (2026) studied this question.

synapsesocial.com/papers/6a508cc46eeac72a437a0aa1https://doi.org/10.5281/zenodo.21261641
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