Incorporating circular economy policies into product supply chains using bilevel optimization -- A case study on coffee packaging

TL;DR

This paper develops a bilevel optimization framework combining economic policies and environmental assessments to promote sustainable, circular coffee packaging supply chains, demonstrating the effectiveness of subsidies over taxes.

Contribution

It introduces a novel bilevel optimization model integrating MILP, LCA, TEA, and circularity metrics for policy evaluation in circular supply chains.

Findings

Subsidies significantly promote low-emission, high-circularity supply chains.

Carbon taxes alone have limited impact on circularity and emissions.

Sensitivity analysis shows key parameters influence policy effectiveness.

Abstract

Transitioning to a Circular Economy requires policies to drive sustainable practices. This study proposes a bilevel optimization framework to evaluate the combined use of carbon taxes and subsidies in promoting circular supply chains under varying budget levels. A case study of the coffee packaging supply chain with an Extended Producer Responsibility scenario is used to demonstrate this approach. The framework captures the hierarchical interaction between a regional government (upper level), which aims to minimize environmental impacts, and coffee companies (lower level), which seek to minimize costs. Two bilevel optimization problems are formulated based on two environmental objectives: (1) minimization of greenhouse gas (GHG) emissions, and (2) maximization of circularity. The model integrates mixed-integer linear programming (MILP) with life cycle assessment (LCA), techno-economic assessment (TEA) and circularity assessment. Results demonstrate that subsidies effectively drive supply chain shifts toward low-emission and high-circularity configurations, while carbon taxes alone have a more limited impact. Sensitivity analyses highlight the influence of key parameters, such as glass washing distance and loss rates, on policy effectiveness. Overall, the study provides a bilevel optimization framework with quantitative insights to support policy design for sustainable circular supply chains.