Resilient Society

Society-Technology-Policy Nexus(複合相互依存性モデリング)

It is obvious that the final objective to assess the resilience of infrastructure systems or social systems against disaster is to protect our lives from the threats and to enhance the chance for our survival. However, in almost all of the related studies, human lives have not been explicitly taken into consideration. Instead, they have focused only on the robustness/vulnerability or recovery efficiency of the lifeline infrastructure systems. In order to discuss social system's resiliency comprehensively including human lives, it is necessary to build a framework for such human-centered resilience assessment. For that purpose, we are now developing a model to describe multiple interdependencies lying behind social systems. This model consists of three social sub-systems, that is lifeline infrastructure systems, service systems and business activities, and our daily lives. This model offers a framework to capture and describe interdependencies within and between these three subsystems.  


Multiple-Interdependency Categorization*

Civil-Industry-Lifeline-Government Nexus 

Sensitivity Analysis to R4 Variables*

Human-Centered Resilience Assessment(人間中心のレジリエンス評価)

In the implementation of the model, it is necessary to consider both structures and processes in the social systems. We implemented system structure by network model and process by agent-based model. Lifeline networks are implemented as simple networks with nodes and links where the reachability of a node  in the graph from any source nodes determines the availability of the lifeline at that node. Service and company agents, citizens, and restoration agents move along the road and transportation networks based on their purpose. Each citizen agent has preferences and rates some specific services over others, which enables to assess individual-life resilience against disaster. Resilience triangles of the social systems are drawn from the simulation under the optimized recovery plan obtained by genetic algorithms (GA). The results present a simple outcome that it is necessary to consider such multiple interdependencies to enhance the resilience of social systems. The result also suggests that it is possible to improve social systems resilience not only by reinforcing critical  infrastructures, but also redesigning the activities of service and company agents. Besides, we are applying a co-evolutional method to optimize civil, industry, and lifeline resilience at the same time considering the complicated multiple interdependency.


Recovery Simulation Considering Multiple Interdependencies

Co-Evolution of Civil, Industry, and Lifeline Resilience*

Optimization by GA and GP*