A framework for modeling interdependencies among households, businesses, and infrastructure systems; and their response to disruptions

TL;DR

This paper develops a dynamic agent-based framework to model interdependencies among households, businesses, and infrastructure systems, and tests their responses to various disruptions through simulation experiments.

Contribution

It introduces a novel agent and network model that captures resource exchanges and responses to disruptions in urban systems.

Findings

The model successfully simulates responses to different disruption scenarios.

Disruption of infrastructure links and production processes has the most severe impact.

Identifies future research directions in network topology and resource allocation mechanisms.

Abstract

Urban systems, composed of households, businesses, and infrastructures, are continuously evolving and expanding. This has several implications because the impacts of disruptions, and the complexity and interdependence of systems, are rapidly increasing. Hence, we face a challenge in how to improve our understanding about the interdependencies among those entities, as well as their responses to disruptions. The aims of this study were to (1) create an agent that mimics the metabolism of a business or household that obtains supplies from and provides output to infrastructure systems; (2) implement a network of agents that exchange resources, as coordinated with a price mechanism; and (3) test the responses of this prototype model to disruptions. Our investigation resulted in the development of a business/household agent and a dynamically self-organizing mechanism of network coordination under disruption based on costs for production and transportation. Simulation experiments confirmed the feasibility of this new model for analyzing responses to disruptions. Among the nine disruption scenarios considered, in line with our expectations, the one combining the failures of infrastructure links and production processes had the most negative impact. We also identified areas for future research that focus on network topologies, mechanisms for resource allocation, and disruption generation.