Abstract

Plastic pollution has become a major environmental challenge. Despite the availability of various recycling technologies, only a small proportion of plastic waste is currently recycled. Developing an Integrated Plastic Recycling Network (IPRN) offers a promising solution to tackling this issue. Facilitating the exchange of material and energy outputs among system components can enhance recycling efficiency. However, disruption in an IPRN component can trigger cascading effects that impact the whole network. This disruption may include shortages in plastic waste inputs. Thus, identifying optimal operating conditions during such disruptions is crucial. This study builds upon previously developed Mixed-Integer Linear Programming (MILP) models based on enterprise Input-Output (IO) modelling framework to optimize IPRN operations under abnormal conditions. The model is modified to allow input substitution during shortages. The improved model incorporates user-defined substitution conditions, such as redirecting materials from mechanical recycling to pyrolysis or gasification, but not vice-versa. During disruptions, rerouting some inputs to prioritize the most profitable processes can significantly improve the network’s revenue. Application of the model to a case study of an IPRN demonstrates that allowing input substitution reduces the revenue drop from 9% to 2.4% under a 10% supply shortage in mixed plastic wastes. Incorporating flexible input substitution can enhance the robustness of IPRNs and ensure more effective recycling even under crisis conditions.