A combined approximate dynamic programming & simulated annealing optimization method to address community-level food security in the aftermath of disasters

by   Saeed Nozhati, et al.

In the aftermath of an extreme natural hazard, community residents must have access to functioning food retailers to maintain food security. Food security is dependent on supporting critical infrastructure systems, including electricity, potable water, and transportation. An understanding of response of such interdependent networks and the process of post-disaster recovery is the cornerstone of an efficient emergency management plan. In this study, the interconnectedness among different critical facilities, such as electrical power networks, water networks, highway bridges, and food retailers is modeled. The study considers various sources of uncertainty and complexity in the recovery process of a community to capture the stochastic behavior of the spatially distributed infrastructure systems. The study utilizes an approximate dynamic programming (ADP) framework to allocate resources to restore infrastructure components efficiently. The proposed ADP scheme enables us to identify near-optimal restoration decisions at the community level. Furthermore, we employ a simulated annealing (SA) algorithm to complement the proposed ADP framework and to identify near-optimal actions accurately. In the sequel, we use the City of Gilroy, California, USA to illustrate the applicability of the proposed methodology following a severe earthquake. The approach can be implemented efficiently to identify practical policy interventions to hasten recovery of food systems and to reduce adverse food-insecurity impacts for other hazards and communities.


page 1

page 4


A Modified Approximate Dynamic Programming Algorithm for Community-level Food Security Following Disasters

In the aftermath of an extreme natural hazard, community residents must ...

An approximate dynamic programming approach to food security of communities following hazards

Food security can be threatened by extreme natural hazard events for hou...

Near-optimal planning using approximate dynamic programming to enhance post-hazard community resilience management

The lack of a comprehensive decision-making approach at the community-le...

Modeling of Lifeline Infrastructure Restoration Using Empirical Quantitative Data

Disaster recovery is widely regarded as the least understood phase of th...

An Approximate Dynamic Programming Approach to Community Recovery Management (Extended Abstract)

The functioning of interdependent civil infrastructure systems in the af...

A decision support system for addressing food security in the UK

This paper presents an integrating decision support system to model food...

Deep Learning-based Resource Allocation for Infrastructure Resilience

From an optimization point of view, resource allocation is one of the co...