Design and optimization of circular economy networks—A case study of PET

Circular design is a potential means of achieving holistic sustainability. However, doing so requires systematic solution approaches to ensure proper design, evaluation, and implementation. This work proposes a generalized optimization framework for designing and optimizing circular economy (CE) networks under multi-criteria decision-making. We apply the proposed framework to a case study of the polyethylene terephthalate (PET) supply chain, considering various waste valorization pathways. A holistic process superstructure is defined and solved as a mixed integer linear program (MILP) in Pyomo. The optimized objective functions include total annualized cost (TAC), greenhouse gas emissions (GHG), and virgin material consumption. A Pareto analysis serves to elucidate trade-offs between competing objectives. Results show that designing for circularity at inception is favorable over linear network design. Trade-offs are significant between cost and emissions and cost and consumption. Furthermore, chemical and mechanical recycling combined proved to be a dominant strategy for all objectives with high tolerance to cost uncertainty, but lower tolerance to yield uncertainty.