Network Based Modelling for Resilience and Vulnerability of Waste System: Graph Theory Approach

Waste management systems play a crucial role in enhancing resilience by ensuring resource availability and reducing environmental vulnerabilities linked to improper disposal. While there is a great interest in waste system, literature did not look waste system as a network. Thus, existing studies often focus on isolated waste chains or descriptive analyses, overlooking the systemic, networked nature of industrial ecosystems and their exposure to shocks. This paper adopts a graph-theoretic approach to model waste flows as a spatial network of interconnected sectors, where nodes represent waste-generating and waste-utilizing industries, and edges denote material transfer pathways. By conceptualizing waste systems as directed and weighted networks, the study provides a robust analytical framework to assess connectivity, efficiency, and resilience under varying operational conditions. The results, validated through a massive simulation framework of 500 independent experiments, demonstrate how different material allocation strategies dictate system stability. Global sensitivity analysis reveals that recycling efficiency is the primary driver of network resilience, whereas strict purity requirements and linear consumption patterns significantly increase system vulnerability. These findings underscore that waste optimization is a critical component of resilience-building in industrial ecosystems. The study contributes a transferable methodological framework for spatial economics, offering a scalable approach for managing complex resource interdependencies in circular economies.